Open-weight models that run on AMD Instinct MI300X
- Memory 192 GB
- Bandwidth 5300 GB/s
- FP16 dense 1307.4 TFLOPS
- Usable 172.8 GB
Specs: Memory · AMD Instinct™ MI300X Accelerators · Bandwidth · AMD Instinct™ MI300X Accelerators · FP16 dense · AMD Instinct™ MI300X Accelerators
| Fit | Model | Parameters / active | Precision | Memory | Est. speed | Longest context | Runs as |
|---|---|---|---|---|---|---|---|
| ●Runs well | GLM-5.3-Flash Zhipu AI | 321.3B / 18B | IQ4_XS | 267–400 tok/s | 133K | One GPU | |
| ●Runs well | MiMo-V2.5 Xiaomi | 310.8B / 15B | Q4_0 | 275–412 tok/s | 13K | One GPU | |
| ●Runs well | DeepSeek-V4-Flash (2026-07-31) DeepSeek | 304.2B | FP8 (native)maker’s file | 138–207 tok/s | 114K | One GPU | |
| ●Runs well | Hy3 Tencent | 298.8B / 21B | Q4_0 | 183–274 tok/s | 27K | One GPU | |
| ●Runs well | DeepSeek-V4-Flash (2026-04-24) DeepSeek | 290.9B / 13B | IQ4_XS | 347–521 tok/s | 258K | One GPU | |
| ●Runs well | DeepSeek-V4-Flash DeepSeek | 290.9B / 13B | IQ4_XS | 347–521 tok/s | 258K | One GPU | |
| ●Runs well | ERNIE-5.5-Flash-Base Baidu | 286.2B | IQ4_XS | speed not estimated | 510K | One GPU | |
| ●Runs well | Qwen3-VL-235B-A22B-Instruct Alibaba Qwen | 235.7B | Q4_K_M | 172–258 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-VL-235B-A22B-Thinking Alibaba Qwen | 235.7B | Q4_K_M | 172–258 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-235B-A22B-Instruct-2507 Alibaba Qwen | 235.1B / 22B | Q4_K_M | 177–266 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-235B-A22B-Thinking-2507 Alibaba Qwen | 235.1B / 22B | Q4_K_M | 177–266 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-235B-A22B Alibaba Qwen | 235.1B / 22B | Q4_K_Mmaker’s file | 178–267 tok/s | 128K | One GPU | |
| ●Runs well | MiniMax-M2.1 MiniMax | 228.7B | Q4_K_M | 302–453 tok/s | 152K | One GPU | |
| ●Runs well | MiniMax-M2.5 MiniMax | 228.7B | Q4_K_M | 302–453 tok/s | 152K | One GPU | |
| ●Runs well | MiniMax-M2.7 MiniMax | 228.7B | Q4_K_M | 302–453 tok/s | 152K | One GPU | |
| ●Runs well | MiniMax-M2 MiniMax | 228.7B / 10B | Q4_K_M | 325–487 tok/s | 152K | One GPU | |
| ●Runs well | MiniMax-M3.1-Flash MiniMax | 220.5B / 23B | Q5_K_M | 153–229 tok/s | 166K | One GPU | |
| ●Runs well | Step 3.7 Flash StepFun | 201.4B | Q5_K_M | 702–1053 tok/s | 186K | One GPU | |
| ●Runs well | Step 3.5 Flash StepFun | 199.4B / 11B | Q5_K_M | 284–426 tok/s | 194K | One GPU | |
| ●Runs well | Ming-3.0-audio-flash Ant Group | 128.2B / 6.5B | Q8_0 | 363–544 tok/s | 128K | One GPU | |
| ●Runs well | Ling-3.0-flash Ant Group | 127.5B / 5.1B | Q8_0maker’s file | 455–683 tok/s | 250K | One GPU | |
| ●Runs well | Qwen3.5-122B-A10B Alibaba Qwen | 125.1B / 10B | Q8_0 | 245–367 tok/s | 256K | One GPU | |
| ●Runs well | Ling-3.0-flash-VL Ant Group | 124.8B / 5.5B | Q8_0 | 425–637 tok/s | 128K | One GPU | |
| ●Runs well | gpt-oss-120b OpenAI | 116.8B / 5.1B | MXFP4 (native)maker’s file | 840–1260 tok/s | 128K | One GPU | |
| ●Runs well | GLM-4.5-Air Zhipu AI | 110.5B | Q8_0 | 135–202 tok/s | 125K | One GPU | |
| ●Runs well | GLM-4.5V Zhipu AI | 107.7B / 12B | Q8_0 | 185–278 tok/s | 63K | One GPU | |
| ●Runs well | GLM-4.6V Zhipu AI | 107.7B | Q8_0 | 159–238 tok/s | 125K | One GPU | |
| ●Runs well | Ling-2.6-flash Ant Group | 107.5B / 7.4B | Q8_0 | 325–487 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-Next-80B-A3B-Instruct Alibaba Qwen | 81.3B / 3B | Q8_0maker’s file | 796–1194 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-Next-80B-A3B-Thinking Alibaba Qwen | 81.3B / 3B | Q8_0maker’s file | 796–1194 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-Coder-Next Alibaba Qwen | 79.7B / 3B | Q8_0maker’s file | 781–1171 tok/s | 256K | One GPU | |
| ●Runs well | Qwen2.5-VL-72B-Instruct Alibaba Qwen | 73.4B | BF16 (native)maker’s file | 18–27 tok/s | 94K | One GPU | |
| ●Runs well | Qwen2-VL-72B-Instruct Alibaba Qwen | 73.4B | BF16 (native)maker’s file | 18–27 tok/s | 32K | One GPU | |
| ●Runs well | Qwen2.5-72B-Instruct Alibaba Qwen | 72.7B | BF16 (native)maker’s file | 18–27 tok/s | 32K | One GPU | |
| ●Runs well | Qianfan-VL-70B Baidu | 71.8B | BF16 (native)maker’s file | 18–27 tok/s | 32K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Llama-70B DeepSeek | 70.6B | BF16 (native)maker’s file | 18–28 tok/s | 111K | One GPU | |
| ●Runs well | Qwen3.5-35B-A3B Alibaba Qwen | 36B / 3B | BF16 (native)maker’s file | 430–644 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3.6-35B-A3B Alibaba Qwen | 36B / 3B | BF16 (native)maker’s file | 430–644 tok/s | 256K | One GPU | |
| ●Runs well | Qwen2.5-VL-32B-Instruct Alibaba Qwen | 33.5B | BF16 (native)maker’s file | 38–56 tok/s | 125K | One GPU | |
| ●Runs well | Qwen3-VL-32B-Instruct Alibaba Qwen | 33.4B | BF16 (native)maker’s file | 38–58 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-VL-32B-Thinking Alibaba Qwen | 33.4B | BF16 (native)maker’s file | 38–58 tok/s | 128K | One GPU | |
| ●Runs well | Qwen2.5-32B-Instruct Alibaba Qwen | 32.8B | BF16 (native)maker’s file | 39–59 tok/s | 32K | One GPU | |
| ●Runs well | Qwen2.5-Coder-32B-Instruct Alibaba Qwen | 32.8B | BF16 (native)maker’s file | 39–59 tok/s | 32K | One GPU | |
| ●Runs well | QwQ-32B Alibaba Qwen | 32.8B | BF16 (native)maker’s file | 39–59 tok/s | 40K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Qwen-32B DeepSeek | 32.8B | BF16 (native)maker’s file | 39–59 tok/s | 32K | One GPU | |
| ●Runs well | Qwen3-32B Alibaba Qwen | 32.8B | BF16 (native)maker’s file | 39–59 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-Omni-30B-A3B-Captioner Alibaba Qwen | 31.7B | BF16 (native)maker’s file | 268–402 tok/s | 64K | One GPU | |
| ●Runs well | Gemma 4 31B IT Google | 31.3B | BF16 (native)maker’s file | 41–61 tok/s | 250K | One GPU | |
| ●Runs well | GLM-4.7-Flash Zhipu AI | 31.2B | BF16 (native)maker’s file | 246–368 tok/s | 195K | One GPU | |
| ●Runs well | Qwen3-VL-30B-A3B-Instruct Alibaba Qwen | 31.1B | BF16 (native)maker’s file | 309–463 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-VL-30B-A3B-Thinking Alibaba Qwen | 31.1B | BF16 (native)maker’s file | 309–463 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-30B-A3B-Instruct-2507 Alibaba Qwen | 30.5B / 3.3B | BF16 (native)maker’s file | 358–537 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-30B-A3B-Thinking-2507 Alibaba Qwen | 30.5B / 3.3B | BF16 (native)maker’s file | 358–537 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-30B-A3B Alibaba Qwen | 30.5B / 3.3B | BF16 (native)maker’s file | 358–537 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-Coder-30B-A3B-Instruct Alibaba Qwen | 30.5B / 3.3B | BF16 (native)maker’s file | 358–537 tok/s | 256K | One GPU | |
| ●Runs well | Hy-Memory-30B-A3B Tencent | 30.1B / 3B | BF16 (native)maker’s file | 389–584 tok/s | 63K | One GPU | |
| ●Runs well | Granite Switch 4.1 30B IBM | 30B | BF16 (native)maker’s file | 43–64 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3.5-27B Alibaba Qwen | 27.8B | BF16 (native)maker’s file | 47–71 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3.6-27B Alibaba Qwen | 27.8B | BF16 (native)maker’s file | 47–71 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3.8-27B Alibaba Qwen | 27.8B | BF16 (native)maker’s file | 47–71 tok/s | 256K | One GPU | |
| ●Runs well | Gemma 4 26B A4B IT Google | 25.8B / 3.8B | BF16 (native)maker’s file | 325–488 tok/s | 250K | One GPU | |
| ●Runs well | Magistral Small 1.2 Mistral AI | 24B | BF16 (native)maker’s file | 27–41 tok/s | 125K | One GPU | |
| ●Runs well | Devstral Small 1.0 Mistral AI | 23.6B | BF16 (native)maker’s file | 28–42 tok/s | 125K | One GPU | |
| ●Runs well | Devstral Small 1.1 Mistral AI | 23.6B | BF16 (native)maker’s file | 28–42 tok/s | 125K | One GPU | |
| ●Runs well | Magistral Small 1.0 Mistral AI | 23.6B | BF16 (native)maker’s file | 28–42 tok/s | 39K | One GPU | |
| ●Runs well | Magistral Small 1.1 Mistral AI | 23.6B | BF16 (native)maker’s file | 28–42 tok/s | 39K | One GPU | |
| ●Runs well | ERNIE-4.5-21B-A3B-Thinking Baidu | 21.8B / 3B | BF16 (native)maker’s file | 410–614 tok/s | 128K | One GPU | |
| ●Runs well | GPT OSS 20B OpenAI | 20.9B / 3.6B | MXFP4 (native)maker’s file | 1030–1545 tok/s | 128K | One GPU | |
| ●Runs well | Qwen2.5-14B-Instruct-1M Alibaba Qwen | 14.8B | BF16 (native)maker’s file | 85–128 tok/s | 767K | One GPU | |
| ●Runs well | Qwen2.5-14B-Instruct Alibaba Qwen | 14.8B | BF16 (native)maker’s file | 85–128 tok/s | 32K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Qwen-14B DeepSeek | 14.8B | BF16 (native)maker’s file | 85–128 tok/s | 32K | One GPU | |
| ●Runs well | Qwen3-14B Alibaba Qwen | 14.8B | BF16 (native)maker’s file | 86–129 tok/s | 128K | One GPU | |
| ●Runs well | Gemma 3 12B IT Google | 12.2B | BF16 (native)maker’s file | 97–145 tok/s | 128K | One GPU | |
| ●Runs well | Qwen2.5-Omni-7B Alibaba Qwen | 10.7B | BF16 (native)maker’s file | 116–174 tok/s | 32K | One GPU | |
| ●Runs well | GLM-4.6V-Flash Zhipu AI | 10.3B | BF16 (native)maker’s file | 127–190 tok/s | 125K | One GPU | |
| ●Runs well | Qwen3.5-9B Alibaba Qwen | 9.7B | BF16 (native)maker’s file | 135–203 tok/s | 256K | One GPU | |
| ●Runs well | Qianfan-VL-8B Baidu | 8.8B | BF16 (native)maker’s file | 142–213 tok/s | 32K | One GPU | |
| ●Runs well | Granite Switch 4.1 8B IBM | 8.8B | BF16 (native)maker’s file | 140–210 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-VL-8B-Instruct Alibaba Qwen | 8.8B | BF16 (native)maker’s file | 141–212 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-VL-8B-Thinking Alibaba Qwen | 8.8B | BF16 (native)maker’s file | 141–212 tok/s | 128K | One GPU | |
| ●Runs well | pplx-embed-v2-context-9b Perplexity | 8.4B | FP32 (native)maker’s file | 78–117 tok/s | 256K | One GPU | |
| ●Runs well | Qwen2.5-VL-7B-Instruct Alibaba Qwen | 8.3B | BF16 (native)maker’s file | 155–233 tok/s | 125K | One GPU | |
| ●Runs well | Qwen3-8B Alibaba Qwen | 8.2B | BF16 (native)maker’s file | 151–226 tok/s | 128K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Llama-8B DeepSeek | 8B | BF16 (native)maker’s file | 155–232 tok/s | 125K | One GPU | |
| ●Runs well | Gemma 4 E4B Google | 8B | BF16 (native)maker’s file | 164–246 tok/s | 125K | One GPU | |
| ●Runs well | Ling-3.0-tiny Ant Group | 7.9B / 1.3B | BF16 (native)maker’s file | 937–1406 tok/s | 128K | One GPU | |
| ●Runs well | Qwen2.5-7B-Instruct-1M Alibaba Qwen | 7.6B | BF16 (native)maker’s file | 169–253 tok/s | 977K | One GPU | |
| ●Runs well | Qwen2.5-7B-Instruct Alibaba Qwen | 7.6B | BF16 (native)maker’s file | 169–253 tok/s | 32K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Qwen-7B DeepSeek | 7.6B | BF16 (native)maker’s file | 169–253 tok/s | 32K | One GPU | |
| ●Runs well | Mistral-7B-Instruct-v0.1 Mistral AI | 7.2B | BF16 (native)maker’s file | 170–256 tok/s | 32K | One GPU | |
| ●Runs well | Gemma 4 E2B Google | 5.1B | BF16 (native)maker’s file | 257–385 tok/s | 125K | One GPU | |
| ●Runs well | WeVisOne-VL-4B Tencent | 4.8B | BF16 (native)maker’s file | 244–366 tok/s | 256K | One GPU | |
| ●Runs well | Qianfan-OCR Baidu | 4.7B | BF16 (native)maker’s file | 248–372 tok/s | 31K | One GPU | |
| ●Runs well | Qwen3.5-4B Alibaba Qwen | 4.7B | BF16 (native)maker’s file | 276–415 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-VL-4B-Instruct Alibaba Qwen | 4.4B | BF16 (native)maker’s file | 263–394 tok/s | 250K | One GPU | |
| ●Runs well | Qwen3-4B-Instruct-2507 Alibaba Qwen | 4B | BF16 (native)maker’s file | 286–430 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-4B Alibaba Qwen | 4B | BF16 (native)maker’s file | 286–430 tok/s | 128K | One GPU | |
| ●Runs well | DeepSeek-OCR DeepSeek | 3.3B | BF16 (native)maker’s file | 951–1427 tok/s | 8K | One GPU | |
| ●Runs well | Granite-4.0-H-Micro IBM | 3.2B | BF16 (native)maker’s file | 411–616 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-1.7B Alibaba Qwen | 2B | BF16 (native)maker’s file | 530–795 tok/s | 40K | One GPU | |
| ●Runs well | DeepSeek-R1-Distill-Qwen-1.5B DeepSeek | 1.8B | BF16 (native)maker’s file | 699–1049 tok/s | 125K | One GPU | |
| ●Runs well | GLM-OCR Zhipu AI | 1.3B | BF16 (native)maker’s file | 831–1247 tok/s | 128K | One GPU | |
| ●Runs well | Qwen3-0.6B Alibaba Qwen | 0.8B | BF16 (native)maker’s file | 1085–1627 tok/s | 40K | One GPU | |
| ●Runs well | EmbeddingGemma 2 Google | 0.7B | BF16 (native)maker’s file | 1680–2521 tok/s | 256K | One GPU | |
| ●Runs well | Qwen3-Embedding-0.6B Alibaba Qwen | 0.6B | BF16 (native)maker’s file | 1243–1865 tok/s | 32K | One GPU | |
| ●Runs well | bge-reranker-v2-m3 BAAI | 0.6B | FP32 (native)maker’s file | 861–1292 tok/s | 8K | One GPU | |
| ●Runs well | bge-m3-unsupervised BAAI | 0.6B | FP32 (native)maker’s file | 861–1292 tok/s | 8K | One GPU | |
| ●Runs well | bge-large-en-v1.5 BAAI | 0.3B | FP32 (native)maker’s file | 1905–2858 tok/s | 512 | One GPU | |
| ●Runs well | bge-reranker-base BAAI | 0.3B | FP32 (native)maker’s file | 2343–3514 tok/s | 514 | One GPU | |
| ●Runs well | bge-base-en-v1.5 BAAI | 0.1B | FP32 (native)maker’s file | 5801–8701 tok/s | 512 | One GPU | |
| ●Runs well | bge-small-en-v1.5 BAAI | 0B | FP32 (native)maker’s file | 18544–27816 tok/s | 512 | One GPU | |
| ○Needs system memory | MiniMax-M3 MiniMax | 427B / 23B | IQ4_XS | 14–21 tok/s | — | 15/60 layers in system memory | |
| ○Needs system memory | Qwen3.5-397B-A17B Alibaba Qwen | 403.4B / 17B | Q4_0 | 18–27 tok/s | — | 15/60 layers in system memory | |
| ○Needs system memory | GLM-4.5 Zhipu AI | 358.3B | IQ4_XS | 19–29 tok/s | — | 9/92 layers in system memory | |
| ○Needs system memory | GLM-4.7 Zhipu AI | 358.3B | IQ4_XS | 19–29 tok/s | — | 9/92 layers in system memory | |
| ○Needs system memory | GLM-4.6 Zhipu AI | 356.8B | Q4_0 | 14–20 tok/s | — | 13/92 layers in system memory |
Estimates from the makers’ Hugging Face repositories (as of 2026-11-06); filtered views aren’t indexed. How it’s estimated