AMD · datacenter
Instinct MI50 32GB
Instinct MI50 32GB has 32 GB of VRAM at 1024 GB/s — about 29.76 GiB usable after driver and compositor overhead. 2012 of 2118 indexed models fit at 8K context with f16 KV.
Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
32 GB
HBM2
Bandwidth
1024 GB/s
4096-bit bus
Tensor FP16
—
dense
TDP
300 W
text 1727vision language 181video 16image 2embedding 26audio tts 21audio asr 39
What fits at 8K context
largest quantization that fits, per model · 2012 of 2118 indexed
| Model | Best quant | Params | Weights● | KV● | Total in memory◐ | Headroom◐ | tok/s◐ |
|---|---|---|---|---|---|---|---|
| Huihui-Qwen3-Coder-Next-abliteratedMoE | I1-IQ3_XXS | 79.7B | 28.68 GiB | 0.19 GiB | 29.76 GiB | 0.00 GiB | 127±37% |
| MiniCPM-o-2_6 | F32 | 8.7B | 28.37 GiB | 0.44 GiB | 29.76 GiB | 0.00 GiB | 22±26.5% |
| IQuest-Coder-V1-40B-Instruct | I1-Q5_K_M | 39.8B | 26.26 GiB | 2.50 GiB | 29.76 GiB | 0.00 GiB | 22±26.5% |
| GLM-4.5-Air-REAP-82B-A12BMoE | IQ1_M | 81.9B | 27.38 GiB | 1.44 GiB | 29.74 GiB | 0.02 GiB | 66±37% |
| c4ai-command-r-plus-08-2024 | IQ2_XXS | 104B | 26.65 GiB | 2.00 GiB | 29.73 GiB | 0.03 GiB | 23±26.5% |
| NousCoder-14B | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Qwen3-14B-Claude-4.5-Opus-High-Reasoning-Distill | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Qwen3-14B | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Qwen3-14B-abliterated | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Josiefied-Qwen3-14B-abliterated-v3 | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Hermes-4-14B | BF16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Qwen3-14B-Base | F16 | 14.8B | 27.51 GiB | 1.25 GiB | 29.72 GiB | 0.04 GiB | 22±26.5% |
| Salience-1.5-ProMoE | Q6_K_L | 36.0B | 28.66 GiB | 0.16 GiB | 29.72 GiB | 0.04 GiB | 116±37% |
| Qwable-v1MoE | Q6_K_L | 36.0B | 28.66 GiB | 0.16 GiB | 29.72 GiB | 0.04 GiB | 116±37% |
| T-SearchMoE | Q6_K_L | 36.0B | 28.66 GiB | 0.16 GiB | 29.72 GiB | 0.04 GiB | 116±37% |
| Llama-4-Scout-17B-16E-InstructMoEKV unresolved | UD-TQ1_0 | 109B | 27.25 GiB | 1.50 GiB | 29.68 GiB | 0.08 GiB | 72±37% |
| Huihui-GLM-4.7-Flash-abliterated-57BMoE | I1-IQ4_XS | 57.3B | 27.68 GiB | 1.05 GiB | 29.67 GiB | 0.09 GiB | 78±37% |
| Phi-3.5-MoE-instructMoEKV unresolved | Q5_K_L | 41.9B | 27.75 GiB | 1.00 GiB | 29.66 GiB | 0.10 GiB | 59±37% |
| Bernini-R | Q8_0 | 14.3B | 28.71 GiB | 0.00 GiB | 29.66 GiB | 0.10 GiB | 22±26.5% |
| Yi-34B-200K-DARE-megamerge-v8 | Q6_K | 34.4B | 26.78 GiB | 1.88 GiB | 29.64 GiB | 0.12 GiB | 23±26.5% |
| Nous-Hermes-2-Yi-34B | I1-Q6_K | 34.4B | 26.78 GiB | 1.88 GiB | 29.64 GiB | 0.12 GiB | 23±26.5% |
| Nous-Capybara-limarpv3-34B | I1-Q6_K | 34.4B | 26.78 GiB | 1.88 GiB | 29.64 GiB | 0.12 GiB | 23±26.5% |
| Apertus-70B-Instruct-2509 | UD-IQ3_XXS | 70.6B | 26.01 GiB | 2.50 GiB | 29.59 GiB | 0.17 GiB | 23±26.5% |
| Rombo-LLM-V3.0-Qwen-72b | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Qwen2.5-72B-Instruct-abliterated | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Qwen2.5-72B-Instruct-abliterated-v2 | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| HuatuoGPT-o1-72B | IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| MiroThinker-v1.0-72B | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Malaysian-Qwen2.5-72B-Instruct | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Qwen2.5-72B | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| magnum-v4-72b | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| KAT-Dev-72B-Exp | IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Homer-v1.0-Qwen2.5-72B | IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Tower-Plus-72B-ultra-uncensored-heretic | I1-IQ2_S | 72.7B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| Qwen2.5-VL-72B-Instruct | IQ2_S | 73.4B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| UI-TARS-72B-DPO | IQ2_S | 73.4B | 26.02 GiB | 2.50 GiB | 29.55 GiB | 0.21 GiB | 23±26.5% |
| archangel_sft-kto_llama30b | IQ4_XS | 32.5B | 16.28 GiB | 12.19 GiB | 29.43 GiB | 0.33 GiB | 23±26.5% |
| Qwen3.5-88BMoE | I1-Q2_K_S | 87.7B | 28.30 GiB | 0.19 GiB | 29.41 GiB | 0.35 GiB | 105±37% |
| Kimi-Linear-48B-A3B-InstructMoE | Q4_K_L | 49.1B | 28.26 GiB | 0.24 GiB | 29.40 GiB | 0.36 GiB | 23±26.5% |
| Gemma-4-Novelist-Eclipse-31B | Q6_K | 32.7B | 25.97 GiB | 2.42 GiB | 29.37 GiB | 0.39 GiB | 23±26.5% |
| Gemma-4-31B-StyleTune | Q6_K | 32.7B | 25.97 GiB | 2.42 GiB | 29.37 GiB | 0.39 GiB | 23±26.5% |
| MiniMax-M2.1-REAP-139B-A10BMoE | I1-IQ1_S | 139B | 26.55 GiB | 1.94 GiB | 29.37 GiB | 0.39 GiB | 70±37% |
| m51Lab-MiniMax-M2.7-REAP-139B-A10BMoE | I1-IQ1_S | 139B | 26.55 GiB | 1.94 GiB | 29.37 GiB | 0.39 GiB | 70±37% |
| Apriel-1.6-15b-Thinker | BF16 | 14.9B | 26.88 GiB | 1.50 GiB | 29.33 GiB | 0.43 GiB | 23±26.5% |
| Assistant_Pepe_70B | Q2_K | 70.6B | 25.79 GiB | 2.50 GiB | 29.32 GiB | 0.44 GiB | 23±26.5% |
| Wizard-Vicuna-30B-Uncensored | I1-IQ4_XS | 32.5B | 16.15 GiB | 12.19 GiB | 29.31 GiB | 0.45 GiB | 23±26.5% |
| Hunyuan-A13B-InstructMoE | Q2_K | 80.4B | 27.40 GiB | 1.00 GiB | 29.29 GiB | 0.47 GiB | 23±26.5% |
| ALIA-40b-fc-2606 | I1-Q5_K_M | 40.4B | 26.78 GiB | 1.50 GiB | 29.29 GiB | 0.47 GiB | 23±26.5% |
| ALIA-40b-instruct-2606 | I1-Q5_K_M | 40.4B | 26.78 GiB | 1.50 GiB | 29.29 GiB | 0.47 GiB | 23±26.5% |
| Qwen3-Coder-NextMoE | UD-IQ3_S | 79.7B | 27.65 GiB | 0.75 GiB | 29.29 GiB | 0.47 GiB | 109±37% |
| Hermes-4-70B | UD-IQ3_XXS | 70.6B | 25.76 GiB | 2.50 GiB | 29.28 GiB | 0.48 GiB | 23±26.5% |
| Llama-3.3-70B-Instruct | UD-IQ3_XXS | 70.6B | 25.76 GiB | 2.50 GiB | 29.28 GiB | 0.48 GiB | 23±26.5% |
| DeepSeek-R1-Distill-Llama-70B | UD-IQ3_XXS | 70.6B | 25.76 GiB | 2.50 GiB | 29.28 GiB | 0.48 GiB | 23±26.5% |
| Darwin-35B-A3B-OpusMoE | Q6_K_L | 36.0B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| Aurora-Code-1MoE | Q6_K_L | 34.7B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| grug-35b-v2MoE | Q6_K_L | 35.1B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| grug-35bMoE | Q6_K_L | 35.1B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| WorldSim-Opus-3.6-35B-A3BMoE | Q6_K_L | 35.1B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| Qwen3.6-35B-A3B-AnkoMoE | Q6_K_L | 35.1B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
| KAT-Coder-V2.5-DevMoE | Q6_K_L | 34.7B | 28.22 GiB | 0.16 GiB | 29.28 GiB | 0.48 GiB | 117±37% |
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 Instinct MI50 32GB run?
- 2012 of 2118 indexed open-weight models fit a Instinct MI50 32GB at 8,192 context with f16 KV cache, the largest being Huihui-Qwen3-Coder-Next-abliterated at I1-IQ3_XXS. That covers text, vision-language, image, video and speech models.
- How much usable memory does a Instinct MI50 32GB actually have?
- Its nameplate is 32 GB, but about 29.76 GiB is available to a model once driver and compositor overhead is accounted for.
- Is a Instinct MI50 32GB fast for local AI?
- Its memory bandwidth is 1024 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.