AMD · unified x86
AMD Ryzen AI Max 390 (Radeon 8050S)
AMD Ryzen AI Max 390 (Radeon 8050S) has 32 GB of VRAM at 256 GB/s — about 22.32 GiB usable after driver and compositor overhead. 1883 of 2118 indexed models fit at 32K context with f16 KV. Note only 24 GB of its 32 GB is allocatable to the GPU.
Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
32 GB
LPDDR5X-8000
Bandwidth
256 GB/s
256-bit bus
Tensor FP16
—
dense
TDP
120 W
vision language 173text 1606image 2audio tts 21audio asr 39video 16embedding 26
What fits at 32K context
largest quantization that fits, per model · 1883 of 2118 indexed
| Model | Best quant | Params | Weights● | KV● | Total in memory◐ | Headroom◐ | tok/s◐ |
|---|---|---|---|---|---|---|---|
| Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved | Q6_K | 27.4B | 21.24 GiB | 2.00 GiB | 24.00 GiB | 0.00 GiB | 6±25% |
| Qwen3.5-27B-uncensored-heretic-v2-Native-MTP-Preserved | Q6_K | 27.4B | 21.24 GiB | 2.00 GiB | 24.00 GiB | 0.00 GiB | 6±25% |
| OLMo-2-1124-7B-Instruct | Q8_0 | 7.3B | 7.23 GiB | 16.00 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Smilodon-9B-v1 | F16 | 10.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| bella-bartender-v2 | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Gemma-The-Writer-9B-HERETIC-Uncensored-Abliterated | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Gemma-2-9B-It-SPPO-Iter3 | BF16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| G2-Darkest-Writer-Dirty-Shirley-9B-v2 | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| G2-Darkest-Writer-9B-v1 | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Gemma-SEA-LION-v3-9B-IT | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Tiger-Gemma-9B-v3 | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| gemma-2-9b-it | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| magnum-v4-9b | F16 | 9.2B | 17.22 GiB | 5.99 GiB | 23.95 GiB | 0.05 GiB | 6±25% |
| Qwen3-VL-30B-A3B-ThinkingMoE | Q5_K_M | 31.1B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| MiroThinker-v1.0-30BMoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| Qwen3-30B-A3BMoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| Qwen3-30B-A3B-Instruct-2507MoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| Qwen3-30B-A3B-Thinking-2507MoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| Pantheon-Proto-RP-1.8-30B-A3BMoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| Tongyi-DeepResearch-30B-A3BMoE | Q5_K_M | 30.5B | 20.25 GiB | 3.00 GiB | 23.94 GiB | 0.06 GiB | 15±37% |
| codegeex4-all-9b | IQ2_XXS | 9.4B | 3.19 GiB | 20.00 GiB | 23.94 GiB | 0.06 GiB | 6±25% |
| glm-4-9b-chat | IQ2_XXS | 9.4B | 3.19 GiB | 20.00 GiB | 23.93 GiB | 0.07 GiB | 6±25% |
| Qwen3-Coder-30B-A3B-InstructMoE | Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Salience-1.5-FlashMoE | I1-Q5_K_M | 31.1B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Huihui-Qwen3-VL-30B-A3B-Instruct-abliteratedMoE | I1-Q5_K_M | 31.1B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-VL-30B-A3B-InstructMoE | Q5_K_M | 31.1B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-30B-A3B-Gemini-Pro-High-Reasoning-2507-ABLITERATED-UNCENSOREDMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-30B-A3B-YOYO-V5MoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-30B-A3B-Thinking-2507-Claude-4.5-Sonnet-High-Reasoning-DistillMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Huihui-Qwen3-30B-A3B-Thinking-2507-abliteratedMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Huihui-Qwen3-30B-A3B-Instruct-2507-abliteratedMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-30B-A3B-abliterated-eroticMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Qwen3-30B-A3B-abliteratedMoE | Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.93 GiB | 0.07 GiB | 15±37% |
| Huihui-Qwen3-Coder-30B-A3B-Instruct-abliteratedMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.92 GiB | 0.08 GiB | 15±37% |
| Qwen3-Coder-30B-A3B-Instruct-RTPurboMoE | I1-Q5_K_M | 30.5B | 20.23 GiB | 3.00 GiB | 23.92 GiB | 0.08 GiB | 15±37% |
| Nemotron-Labs-Audex-30B-A3B | Q4_K_M | 32.0B | 23.16 GiB | 0.00 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| Qwen3-Coder-NextMoE | UD-IQ1_M | 79.7B | 20.21 GiB | 3.00 GiB | 23.90 GiB | 0.10 GiB | 17±37% |
| Gemma4-Gutenberg-31B | Q4_K_S | 31.3B | 16.95 GiB | 6.17 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| gemma-4-31B-it | Q4_K_S | 31.3B | 16.95 GiB | 6.17 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| Gemma4-Gutenberg-31B-Heretic | Q4_K_S | 31.3B | 16.95 GiB | 6.17 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| Equinox-31B | Q4_K_S | 31.3B | 16.95 GiB | 6.17 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| gemma-4-31B-it-SDFT-Heretic-RP | Q4_K_S | 30.7B | 16.95 GiB | 6.17 GiB | 23.90 GiB | 0.10 GiB | 6±25% |
| Goetia-26B-A4B-v1.4MoE | I1-Q6_K | 26.0B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| G4-Moonlight-Dusk-26B-A4B-hereticMoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Pantheon-Reasoning-26B-A4B-1.1-hereticMoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| G4-Moonlight-Dusk-26B-A4BMoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Chimera-X-26B-A4BMoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Pantheon-Reasoning-26B-A4B-1.1MoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Gemma-4-26B-A4B-StyleTune-V2MoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Gemma-4-26B-A4B-StyleTuneMoE | I1-Q6_K | 26.5B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| gemma-4-26b-a4b-heretic-styletune-v2-headMoE | I1-Q6_K | 25.8B | 21.65 GiB | 1.54 GiB | 23.88 GiB | 0.12 GiB | 6±25% |
| Qwen3-42B-A3B-2507-Thinking-Abliterated-uncensored-TOTAL-RECALL-v2-Medium-MASTER-CODERMoE | I1-Q3_K_M | 42.4B | 18.97 GiB | 4.19 GiB | 23.86 GiB | 0.14 GiB | 12±37% |
| Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16 | UD-Q5_K_S | 33.0B | 23.10 GiB | 0.00 GiB | 23.85 GiB | 0.15 GiB | 6±25% |
| Devstral-Small-2-24B-Instruct-2512 | Q6_K | 24.0B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Transformed-Journey-24B | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Magistry-24B-v1.1 | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Mergedonia-AETHER-24B-v1a | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Mergedonia-AETHER-24B-v1b | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Slimaki-Tavern-24B-v1.3 | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
| Maginum-Cydoms-24B | I1-Q6_K | 23.6B | 18.02 GiB | 5.00 GiB | 23.84 GiB | 0.16 GiB | 6±25% |
Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.
Questions people ask
- What AI models can a AMD Ryzen AI Max 390 (Radeon 8050S) run?
- 1883 of 2118 indexed open-weight models fit a AMD Ryzen AI Max 390 (Radeon 8050S) at 32,768 context with f16 KV cache, the largest being Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved at Q6_K. That covers text, vision-language, image, video and speech models.
- How much usable memory does a AMD Ryzen AI Max 390 (Radeon 8050S) actually have?
- Its nameplate is 32 GB, but about 22.32 GiB is available to a model once driver and compositor overhead is accounted for, and only 24 GB of the pool can be allocated to the GPU at all.
- Is a AMD Ryzen AI Max 390 (Radeon 8050S) fast for local AI?
- Its memory bandwidth is 256 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.