# Detailed capabilities and feature descriptions

The video decode and encode capabilities are detailed in the following tabs.

Tab QCS6490
Tab QCS8275
Tab QCS9075

Table : Adreno VPU decoder capabilities for QCS6490

| Decoder standard | Supported profile and level | Minimum/Maximum resolution, Maximum frame rate, and bit rate | Maximum supported resolution, frame rate, and bit rate | Limitations/tools not supported |
| --- | --- | --- | --- | --- |
| HEVC | <ul class="simple"><br><li><p>Main profile 8-bit up to level 5.1</p></li><br><li><p>Main profile 10-bit, up to level 5.1, HLG schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 100 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>Maximum 128 slices per frame</p></li><br><li><p>Individual slice-based decoding</p></li><br></ul> |
| H.264 | Constrained baseline, baseline, main, high, constrained high profiles; up to level 5.2 | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 100 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>Flexible macroblock order (FMO)</p></li><br><li><p>Arbitrary slice ordering (ASO)</p></li><br><li><p>Redundant slices (RS)</p></li><br><li><p>Data partition</p></li><br><li><p>Maximum 10 slices per frame</p></li><br><li><p>Interlaced content is not supported</p></li><br></ul> |
| VP9 | <ul class="simple"><br><li><p>Profile 0; 8-bit up to level 5.1</p></li><br><li><p>Profile 2; 10-bit up to level 5.1 HLG/PQ schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 100 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 100 Mbps</p></li><br></ul> | Profile 2; 12-bit is not supported |

Table : Adreno VPU encoder capabilities for QCS6490

| Encoder standard | Supported profile and level and RC modes | Minimum/Maximum resolution, maximum frame rate, and maximum bit rate | Supported resolution, frame rate, bit rate | Limitations/tools not supported |
| --- | --- | --- | --- | --- |
| H.264 | <ul class="simple"><br><li><p>Constrained baseline, baseline, main, high, constrained high profiles; up to level 5</p></li><br><li><p>VBR, CBR, MBR</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 128 × 128</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 240 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 240 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 120 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 30 fps, 100 Mbps</p></li><br><li><p>4096 × 2160 at 30 fps, 100 Mbps</p></li><br></ul> | None |
| HEVC | <ul class="simple"><br><li><p>Main profile 8-bit, up to level 5.0</p></li><br><li><p>Main/High tier VBR, CBR, MBR</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 128 × 128</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 240 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 240 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 120 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 30 fps, 100 Mbps</p></li><br><li><p>4096 × 2160 at 30 fps, 100 Mbps</p></li><br></ul> | Vertical tiling is only enabled for frame width ≥ 960 |

Table : Adreno VPU feature description for QCS6490

| Feature | Description | Codecs | Remarks |
| --- | --- | --- | --- |
| Encoder input color formats | NV12 and QC08C | H.264 and HEVC | None |
| Decoder output color formats | NV12, QC08C, and QC10C | H.264, HEVC, and VP9 | None |
| Rotation | Supports 90, 180, and 270-degree rotation before encoding the frame | H.264 and HEVC | Supports static rotation only |
| Flip | Supports horizontal and vertical flip before encoding the frame | H.264 and HEVC | Supports static and dynamic flip |
| B-frame encode | Up to 1920 × 1088 at 60 fps encode | H.264 and HEVC | The maximum number of B-frames supported between 2 P-frames is 1 |
| Hierarchical-P encode | Up to 5 layers | H.264 and HEVC | None |
| Initial QP override | Supported for I, P and B-frames | H.264 and HEVC | None |
| Slice encode | Yes | H.264 and HEVC | The slice boundary is supported based on the number of bits per slice or the number of macroblocks per slice |
| Intra-refresh | Random refresh mode | H.264 and HEVC | <ul class="simple"><br><li><p>Supported only in 8-bit encoding</p></li><br><li><p>Supported only in the CBR RC mode</p></li><br></ul> |
| Rate control | CBR, VBR, and MBR | H.264 and HEVC | None |
| LTR | 2 frames | H.264 and HEVC | Supported in CBR RC mode |
| Dynamic properties for encoder | Sync frame, bit rate, and fps | H.264 and HEVC | Supported in CBR and VBR RC modes |
| Multichannel support | Up to 16 instances | H.264, HEVC, and VP9 | Subject to maximum macroblock capability and bitrate |

Table : Adreno VPU decoder capabilities for QCS8275

| **Decoder standard** | **Supported profile and level** | **Minimum/Maximum resolution, maximum frame rate, and maximum bit rate** | **Maximum supported resolution, frame rate, and bit rate** | **Limitations/tools not supported** |
| --- | --- | --- | --- | --- |
| HEVC | <ul class="simple"><br><li><p>Main profile 8-bit, up to level 5.1 Main tier, high tier</p></li><br><li><p>Main10, profile up to level 5.1 Main/High tier, HLG schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>4096 × 2160 at 60 fps, 120 Mbps (IBP/IPP)</p></li><br></ul> | Individual slice-based decoding |
| H.264 | Constrained baseline, Baseline, main, high, constrained high profiles; up to level 5.2 | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>4096 × 2160 at 60 fps, 120 Mbps (IBP/IPP)</p></li><br></ul> | <ul class="simple"><br><li><p>Flexible macroblock order (FMO)</p></li><br><li><p>Arbitrary slice ordering (ASO)</p></li><br><li><p>Redundant slices (RS)</p></li><br><li><p>Data partition</p></li><br><li><p>Individual slice-based decoding</p></li><br><li><p>Non-progressive-only content up to 1920 x 1088</p></li><br><li><p>Best effort B-frame decodes are:</p><br><ul><br><li><p>3840 × 2160 at 120 fps</p></li><br></ul><br></li><br></ul> |
| VP9 | <ul class="simple"><br><li><p>Profile 0; 8-bit, up to level 5.1</p></li><br><li><p>Profile2, 10-bit, up to<br>level 5.1, HLG/PQ schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 120 fps</p></li><br><li><p>Maximum bit rate: 50 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 120 fps, 50 Mbps</p></li><br><li><p>1920 × 1088 at 120 fps, 50 Mbps</p></li><br><li><p>3840 × 2160 at 120 fps, 50 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 50 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>Profile 2, 12-bit is not supported</p></li><br><li><p>Individual slice-based decoding</p></li><br></ul> |
| AV1 | <ul class="simple"><br><li><p>Main (Profile-0)</p></li><br><li><p>Maximum level: 5.1</p></li><br><li><p>HLG/PQ schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 240 fps</p></li><br><li><p>Maximum bit rate: 120 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 240 fps, 120 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 120 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 120 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 120 Mbps</p></li><br></ul> | Individual slice-based decoding |

Table : Adreno VPU encoder capabilities for QCS8275

| **Encoder standard** | **Supported profile, level, and RC mode** | **Minimum/Maximum resolution, maximum frame rate, and maximum bit rate** | **Maximum supported resolution, frame rate, and bit rate** | **Limitations/tools not supported** |
| --- | --- | --- | --- | --- |
| H.264 | <ul class="simple"><br><li><p>Constrained baseline, baseline, main, high, constrained high profiles; up to level 5.2</p></li><br><li><p>VBR and CBR</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 128 × 128</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br><li><p>Maximum operating rate: 480</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 88 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 128 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 80 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 92 Mbps</p></li><br></ul> |  |
| HEVC | Main profile 8-bit, up to level 5.1 Main/High tier VBR and CBR | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2160 or 2160 × 4096</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br><li><p>Maximum operating rate: 480</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 62 Mbps</p></li><br><li><p>1920 × 1088 at 240 fps, 90 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 56 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 64 Mbps</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps</p></li><br><li><p>7680 × 4320 at 30 fps, 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>Multislice is enabled</p></li><br></ul> |

Table : Adreno VPU feature description for QCS8275

| **Feature** | **Description** | **Codecs** | **Remarks** |
| --- | --- | --- | --- |
| Encoder input color formats | NV12 and QC08C | H.264 and HEVC | None |
| Decoder output color formats | NV12, QC08C, and QC10C | H.264, HEVC, VP9 and AV1 | None |
| B-frame encode | Up to 1920 × 1088 at 120 fps encode | H.264 and HEVC | The maximum number of B-frames supported between two P-frames is one |
| Initial QP override | Supported for I, P, and B- frames | H.264 and HEVC | None |
| Rate control | CBR and VBR | H.264 and HEVC | None |
| Dynamic properties for encoder | Sync frame, bit rate, and fps | H.264 and HEVC | Supported in CBR and VBR RC modes |
| Multichannel support | Up to 16 instances | H.264, HEVC, VP9, and AV1 | Subject to maximum macroblock capability and bitrate |

Note

End-to-end functionality using [IM SDK](https://docs.qualcomm.com/bundle/publicresource/topics/80-70017-50/overview.html) is validated up to 3840 × 2160 resolution.

Table : Adreno VPU decoder capabilities for QCS9075

| Decoder standard | Supported profile and level | Minimum/maximum resolution, Maximum frame rate, and bit rate | Maximum supported resolution, frame rate, and bit rate | Limitations/tools not supported |
| --- | --- | --- | --- | --- |
| HEVC | <ul class="simple"><br><li><p>Main profile 8-bit, up to level 6.2, main tier, high tier</p></li><br><li><p>Main10 profile up to level 6.2 Main/High tier HLG schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 8192 × 4320 or 4320 × 8192</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>3840 × 2160 at 240 fps, 80 Mbps (IBP/IPP)</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>4096 × 2160 at 120 fps, 80 Mbps (IBP/IPP)</p></li><br><li><p>7680 × 4320 at 30 fps, 120 Mbps (IBP/IPP)</p></li><br><li><p>7680 × 4320 at 60 fps, 80 Mbps (IBP/IPP)</p></li><br><li><p>8192 × 4320 at 30 fps, 120 Mbps (IBP/IPP)</p></li><br><li><p>8192 × 4320 at 48 fps, 80 Mbps (IBP/IPP)</p></li><br></ul> | Individual slice-based decoding |
| H.264 | Constrained baseline, baseline, main, high, constrained high profiles; up to level 6.1 | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 8192 × 4320 or 4320 × 8192</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 220 Mbps (CAVLC), 160 Mbps (CABAC)</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>3840 × 2160 at 240 fps, 80 Mbps (IPP)</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps (IBP/IPP)</p></li><br><li><p>4096 × 2160 at 120 fps, 80 Mbps (IPP)</p></li><br><li><p>7680 × 4320 at 60 fps, 80 Mbps (IPP)</p></li><br><li><p>7680 × 4320 at 30 fps, 120 Mbps (IBP/IPP)</p></li><br><li><p>8192 × 4320 at 30 fps, 120 Mbps (IPP)</p></li><br><li><p>8192 × 4320 at 48 fps, 80 Mbps (IPP)</p></li><br></ul> | <ul class="simple"><br><li><p>Flexible macroblock order (FMO)</p></li><br><li><p>Arbitrary slice ordering (ASO)</p></li><br><li><p>Redundant slices (RS)</p></li><br><li><p>Data partition</p></li><br><li><p>Individual slice-based decoding</p></li><br><li><p>Non-progressive-only content up to 1920 × 1088</p></li><br><li><p>Best effort B-frame decodes are:</p><br><ul><br><li><p>3840 × 2160 at 240 fps</p></li><br><li><p>4096 × 2160 at 120 fps</p></li><br><li><p>7680 × 4320 at 60 fps</p></li><br><li><p>8192 × 4320 at 30/48 fps</p></li><br></ul><br></li><br></ul> |
| VP9 | <ul class="simple"><br><li><p>Profile 0; 8-bit up to level 5.1</p></li><br><li><p>Profile2, 10-bit, up to level 5.1, HLG/PQ schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 4096 × 2304 or 2304 × 4096</p></li><br><li><p>Maximum frame rate: 120 fps</p></li><br><li><p>Maximum bit rate: 100 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 120 fps, 100 Mbps</p></li><br><li><p>1920 × 1088 at 120 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 60 fps, 100 Mbps</p></li><br><li><p>3840 × 2160 at 240 fps, 30 Mbps</p></li><br><li><p>4096 × 2160 at 60 fps, 100 Mbps</p></li><br><li><p>4096 × 2304 at 60 fps, 100 Mbps</p></li><br></ul> | Profile 2, 12-bit is not supported |
| AV1 | <ul class="simple"><br><li><p>Main (Profile-0), 8-bit and 10-bit</p></li><br><li><p>Max level: 6.1</p></li><br><li><p>HLG/PQ schemes</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 8192 × 4320 or 4320 × 8192</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 120 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 120 Mbps</p></li><br><li><p>1920 × 1088 at 480 fps, 120 Mbps</p></li><br><li><p>3840 × 2160 at 240 fps, 120 Mbps</p></li><br><li><p>3840 × 2160 at 120 fps, 120 Mbps</p></li><br><li><p>4096 × 2160 at 120 fps, 120 Mbps</p></li><br><li><p>7680 × 4320 at 30 fps, 120 Mbps</p></li><br><li><p>7680 × 4320 at 60 fps, 120 Mbps</p></li><br><li><p>8192 × 4320 at 30 fps, 120 Mbps</p></li><br><li><p>8192 × 4320 at 48 fps, 120 Mbps</p></li><br></ul> | Individual slice-based decoding |

Table : Adreno VPU encoder capabilities for QCS9075

| Encoder standard | Supported profile, level, and RC modes | Minimum/Maximum resolution, maximum frame rate, and maximum bit rate | Supported resolution, frame rate, bit rate | Limitations/tools not supported |
| --- | --- | --- | --- | --- |
| H.264 | <ul class="simple"><br><li><p>Constrained baseline, baseline, main, high, constrained high profiles; up to level 6.0</p></li><br><li><p>VBR and CBR</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 128 × 128</p></li><br><li><p>Maximum resolution: 8192 × 4320 or 4320 × 8192</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 220 Mbps (CAVLC), 160 Mbps (CABAC)</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps</p></li><br><li><p>7680 × 4320 at 30 fps, 160 Mbps</p></li><br></ul> | Individual encoded slice delivery per buffer |
| HEVC | <ul class="simple"><br><li><p>Main profile 8bit, up to level 6.0, 6.1, Main/High tier</p></li><br><li><p>VBR and CBR</p></li><br></ul> | <ul class="simple"><br><li><p>Minimum resolution: 96 × 96</p></li><br><li><p>Maximum resolution: 8192 × 4320 or 4320 × 8192</p></li><br><li><p>Maximum frame rate: 480 fps</p></li><br><li><p>Maximum bit rate: 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>1280 × 720 at 480 fps, 160 Mbps</p></li><br><li><p>1920 × 1088 at 480 fps, 160 Mbps</p></li><br><li><p>3840 × 2160 at 120 fps, 160 Mbps</p></li><br><li><p>7680 × 4320 at 30 fps, 160 Mbps</p></li><br></ul> | <ul class="simple"><br><li><p>Individual encoded slice delivery per buffer</p></li><br><li><p>Multislice is enabled</p></li><br></ul> |

| <br>Multichannel/Resolution/ fps/Codec | <br>Use case combination | <br>Recommended bit rate per session (Mbps) | <br>Recommended bit rate per session (Mbps) | <br>Recommended bit rate per session (Mbps) | <br>Recommended bit rate per session (Mbps) |
| --- | --- | --- | --- | --- | --- |
| <br>Multichannel/Resolution/ fps/Codec | <br>Use case combination | H.264 (CAVLC) | H.264 (CABAC) | HEVC | AV1 (Decoder only) |
| 24x for 1920 × 1088 at 30fps, any supported codec combination | Decode only (or) Decode + Encode (or) Encode only | 9.17 | 7.92 | 7.92 | 5 |
|  |  |  |  |  |  |

Table : Adreno VPU feature description for QCS9075

| Feature | Description | Codecs | Remarks |
| --- | --- | --- | --- |
| Encoder input color formats | NV12 and QC08C | H.264 and HEVC | None |
| Decoder output color formats | NV12, QC08C, and QC10C | H.264, HEVC, VP9 and AV1 | None |
| B-frame encode | Up to 3840 × 2160 at 60 fps encode | H.264 and HEVC | The maximum number of B-frames supported between two P-frames is one |
| Initial QP override | Supported for I, P, and B-frames | H.264 and HEVC | None |
| Rate control | CBR and VBR | H.264 and HEVC | None |
| Dynamic properties for encoder | Sync frame, bit rate, and fps | H.264 and HEVC | Supported in CBR and VBR RC modes |
| Multichannel support | Up to 24 instances | H.264, HEVC, VP9, and AV1 | See [Adreno VPU multichannel capabilities for QCS9075](https://docs.qualcomm.com/doc/80-70017-20/topic/feature-descriptions.html#adrenovpumulti) |

Note

End-to-end functionality using [IM SDK](https://docs.qualcomm.com/bundle/publicresource/topics/80-70017-50/overview.html) is validated up to 3840 × 2160 resolution.

The supported encoder feature descriptions are as follows:

**B-frame encode**

B-frame is a type of frame that uses both previous and future frames as data reference to obtain the highest amount of data compression. The Adreno VPU can encode frames with adaptive B type to obtain the highest possible compression without compromising on the video quality.

**Encoder initial QP override**

Video encoding involves mapping signal levels to discrete values that are easily compressed. Quantization is a lossy process, and the levels of quantization govern the quality compared to compression. Encoders start with a default Quantization Parameter (QP) at the beginning. Based on the configured bit rate and scene complexity, encoders arrive at the right QP value by continuously monitoring the complexity and redundancy across frames. It may take a few seconds for the encoder to reach a steady state and predict the correct QP value that matches the target bit rate (also known as rate convergence).

**Hierarchical-P encode**

With the Hierarchical-P (Hier-P) feature, the encoder organizes the frames into multiple layers, with frames of one layer only referencing frames from the lower layers as shown in the following figure. The lowest layer, also known as layer 0 or the base layer, is the only exception.

![../../_images/Layer-encoding.jpg](data:image/jpeg;base64,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**Figure : Hier-P layer encoding pattern**

In this figure, TL-0 represents the base layer, and the remaining layers represent the enhancement layers. Hier-P improves error resilience and temporal scalability. The Hier-P feature is useful for video telephony (VT) or videoconferencing applications that involve channel errors. Hier-P allows you to control error propagation by selectively dropping the enhancement layers.

**Slice encode**

Encoders can compress a frame with an independently decodable Group-of-Blocks (GOBs), also known as slices. If there is a data loss or corruption, each slice is independently decodable, and is intended to be a unit of recovery. The following are the advantages of introducing slices in an encoded frame:

- A corrupt slice can be ignored and skipped to a next slice, thus restricting the corruption to a part of the frame instead of the entire frame.
- Slices can be sized to fit within a network packet to help with transmission.
- Erroneous slices can be retransmitted instead of sending the entire frame.
- Applications can use slices to reduce latency in real-time communication. Slices can be transmitted and decoded in parallel, without having to wait for the entire frame to be encoded.

Slices also work as resynchronization markers because the decoders can resume from the next slice (marker) when there are bit errors. The H.264 and HEVC encoders support slicing on Qualcomm Linux. A slice boundary can be specified as the number of bits per slice or the number of macroblocks per slice.

**Intra refresh**

The intra-refresh feature helps in reducing the channel loss in streaming and casting applications that favor a constant bit rate. The Adreno VPU supports random intra-refresh mode.

**Video encoder preprocessing**

When a YUV frame must be rotated or flipped, applications can use the Adreno VPU to perform the rotation or flip operations before encoding the YUV frame. The Adreno VPU performs the rotation or flip operation without consuming extra power.

**Rate control**

The following table lists the supported rate control algorithms:

| Rate control mode | Description |
| --- | --- |
| Variable bit rate (VBR) | <ul class="simple"><br><li><p>Minimizes the frame-by-frame video quality fluctuation</p></li><br><li><p>Camcorder and Wi-Fi display are the example use cases</p></li><br></ul> |
| Constant bit rate (CBR) | <ul class="simple"><br><li><p>Reduces bit rate fluctuation</p></li><br><li><p>Used for real-time communication with channel bandwidth limitation</p></li><br><li><p>Video telephony and streaming are the example use cases</p></li><br></ul> |
| Maximum bit rate (MBR) | <ul class="simple"><br><li><p>Limits the bit rate while maintaining flexibility and may bounce up and down within the set target</p></li><br><li><p>Bit rate increases when the activity in a scene increases within a maximum limit</p></li><br><li><p>Integrated with a smart bit allocation (SBA) feature to achieve better quality at a lower bit rate</p></li><br></ul> |

**Long Term Reference (LTR) support**

Video compression works by eliminating redundancies within the frame (intra-frame) and between the frames (inter-frame). Previously, the encoded frames that used to serve as a basis to derive future frames were known as reference frames.

The following are the two types of reference frames that allow advanced encoding applications to control the way the reference frames are stored and referred:

- **Short-Term Reference (STR)**: Recent frames are maintained in a reference buffer list from the newest to the oldest. The encoder automatically manages frames using STRs for reference, and deletes them from a stored list when they are no longer used.
- **Long-Term Reference (LTR)**: Frames that the application can save, use, and remove. The LTR frames are used to improve quality and ensure error resiliency in video communication. The maximum number of frames that can be marked with LTR frames depends on the device
capability.

LTR frames are useful in error-prone channels. Referring to LTR in error-prone channels reduces the possibility of drift errors due to channel losses. The receiver must confirm that the LTR is received successfully and that it can request a new LTR when an error occurs. The network protocols have checksums that can confirm this behavior, along with the decoder corruption flags. New LTR frames are generated from the sender until the receiver confirms that a successful LTR is received.

LTR frames are also useful in videos with scene changes where an LTR with the previous scene can be preserved. If that scene comes back, then the LTR can be used effectively.

At the start of the new Group-of-pictures (GOP), the encoder automatically fills the LTR slots, and the first slot (slot number 0) is filled with an IDR frame. However, an application can explicitly send an LTR mark request to mark the LTR frames in the appropriate slots. The following image shows the flow diagram for LTR usage, and the way the LTR frames can be marked and used on an H.264 or HEVC encoder:

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transform="translate(463.75,-81.25)">		<title></title>		<path d="M-0 532.25 L-10.96 532.25" class="st6"></path>	</g>	<g id="shape77-132" v:mid="77" v:groupcontext="shape" v:layermember="0" transform="translate(606.75,-90.25)">		<title></title>		<desc>Use as reference</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="0.750016" cy="433.5" width="79.04" height="18.8036"></v:textrect>		<path d="M0 541.25 L0 360.75 L11.96 360.75" class="st6"></path>		<rect v:rectcontext="textBkgnd" x="-33.5164" y="428.1" width="68.5327" height="10.7998" class="st10"></rect>		<text x="-33.52" y="436.2" class="st5" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>Use as reference</text>		</g>	<g id="shape78-139" v:mid="78" v:groupcontext="shape" v:layermember="0" transform="translate(606.75,-81.25)">		<title></title>		<path d="M0 532.25 L18 532.25" class="st8"></path>	</g>	<g id="shape79-142" v:mid="79" v:groupcontext="shape" v:layermember="0" transform="translate(715.75,-108.25)">		<title></title>		<desc>Use as reference</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="0" cy="451.875" width="79.04" height="18.8036"></v:textrect>		<path d="M0 541.25 L0 381.5 L11.96 381.5" class="st6"></path>		<rect v:rectcontext="textBkgnd" x="-34.2664" y="446.475" width="68.5327" height="10.7998" class="st10"></rect>		<text x="-34.27" y="454.58" class="st5" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>Use as reference</text>		</g>	<g id="shape80-149" v:mid="80" v:groupcontext="shape" v:layermember="0" transform="translate(715.75,-99.25)">		<title></title>		<path d="M0 532.25 L18 532.25" class="st8"></path>	</g>	<g id="shape81-152" v:mid="81" v:groupcontext="shape" v:layermember="0" transform="translate(788.25,-126.25)">		<title></title>		<desc>Mark as LTR</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="-0.500001" cy="469.25" width="62.02" height="18.8036"></v:textrect>		<path d="M-0.5 541.25 L-0.5 388.25 L-17.5 388.25" class="st8"></path>		<rect v:rectcontext="textBkgnd" x="-26.2542" y="463.85" width="51.5083" height="10.7998" class="st10"></rect>		<text x="-26.25" y="471.95" class="st5" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>Mark as LTR</text>		</g>	<g id="shape82-157" v:mid="82" v:groupcontext="shape" v:layermember="0" transform="translate(769.75,-117.25)">		<title></title>		<path d="M6.68 532.25 L7.04 532.25 L18 532.25" class="st11"></path>	</g>	<g id="shape86-163" v:mid="86" v:groupcontext="shape" transform="translate(301.75,-486.25)">		<title></title>		<desc>2. Check if the frame was marked LTR</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st2"></rect>		<text x="15.53" y="520.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>2. Check if the frame was marked <v:lf></v:lf><tspan x="80.55" dy="1.2em" class="st4">LTR</tspan></text>		</g>	<g id="shape87-167" v:mid="87" v:groupcontext="shape" transform="translate(544.75,-486.25)">		<title></title>		<desc>4. Check if the LTR at slot # 0 was used as a reference</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st2"></rect>		<text x="13.85" y="520.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>4. Check if the LTR at slot # 0 was <tspan x="45.81" dy="1.2em" class="st4">used as a reference</tspan></text>		</g>	<g id="shape88-171" v:mid="88" v:groupcontext="shape" transform="translate(193.75,-405.25)">		<title></title>		<desc>1. Mark frame as LTR at slot # 0</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st12"></rect>		<text x="18.59" y="526.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>1. Mark frame as LTR at slot # 0</text>		</g>	<g id="shape89-174" v:mid="89" v:groupcontext="shape" transform="translate(481.75,-405.25)">		<title></title>		<desc>3. Mark frame as LTR at slot # 0</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st2"></rect>		<text x="18.59" y="526.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>3. Mark frame as LTR at slot # 0</text>		</g>	<g id="shape90-177" v:mid="90" v:groupcontext="shape" transform="translate(733.75,-441.25)">		<title></title>		<desc>5a. Using LTR at slot # 1 as reference</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st2"></rect>		<text x="28.3" y="520.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>5a. Using LTR at slot # 1 as <v:lf></v:lf><tspan x="68.88" dy="1.2em" class="st4">reference</tspan></text>		</g>	<g id="shape91-181" v:mid="91" v:groupcontext="shape" transform="translate(733.75,-387.25)">		<title></title>		<desc>5b. Mark frame as LTR at slot # 2</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="90" cy="523.25" width="180" height="36"></v:textrect>		<rect x="0" y="505.25" width="180" height="36" class="st2"></rect>		<text x="15.8" y="526.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>5b. Mark frame as LTR at slot # 2</text>		</g>	<g id="shape92-184" v:mid="92" v:groupcontext="shape" transform="translate(8.99999,-270.25)">		<title></title>		<desc>Encoder</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="27.125" cy="532.25" width="54.26" height="18"></v:textrect>		<rect x="0" y="523.25" width="54.25" height="18" class="st2"></rect>		<text x="8.5" y="535.25" class="st3" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>Encoder</text>		</g>	<g id="shape93-187" v:mid="93" v:groupcontext="shape" transform="translate(18.25,-117.25)">		<title></title>		<desc>Slot# 2</desc>		<v:textblock v:margins="rect(4,4,4,4)"></v:textblock>		<v:textrect cx="22.5" cy="532.25" width="45" height="18"></v:textrect>		<rect x="0" y="523.25" width="45" height="18" class="st2"></rect>		<text x="10.05" y="534.65" class="st13" v:langid="1033"><v:paragraph v:horizalign="1"></v:paragraph><v:tablist></v:tablist>Slot# 2</text>		</g>	<g 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</svg>

**Figure : Long-Term Reference encoding**

**Dynamic encoder properties**

The Adreno VPU encoder supports dynamic change of properties such as bit rate, frame rate, and sync frame. This support enables the application to change the properties and helps in improved visual experience, video data adjusting to network conditions, and minimizing the loss of data during transmission.

Last Published: Dec 30, 2024

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Source: [https://docs.qualcomm.com/doc/80-70017-20/topic/feature-descriptions.html](https://docs.qualcomm.com/doc/80-70017-20/topic/feature-descriptions.html)