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Can the NVIDIA T1000 8GB run MiMo V2.6 Pro (1T-A42B)?

68Good quality (B) · 68 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking.

No, it doesn’t fit

No. MiMo V2.6 Pro (1T-A42B) needs about 411 GB even at Q2_K; the NVIDIA T1000 8GB has 8.0 GB usable.

Download MiMo V2.6 Pro (1T-A42B)

Recommended: Q2_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q2_K file (opens in a new tab)

huggingface.co/ggml-org/MiMo-V2.6-Pro-RL-GGUF (opens in a new tab)

ollama run hf.co/ggml-org/MiMo-V2.6-Pro-RL-GGUF:Q2_K

Original weights · Hugging Face

Full-precision files from Xiaomi, for fine-tuning, vLLM, Transformers.

huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL (opens in a new tab)

No sign-in needed.

Links checked 2 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 68Good quality (B) · 68 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at Q2_K, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Won't run
How well it runs on the NVIDIA T1000 8GB: speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.9.2 / 45
Memory fitFull marks when everything sits in GPU memory; fewer when part spills to system RAM.0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.0.0 / 15
Match score9.2 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Every quantization on the NVIDIA T1000 8GB

Quant Memory needed Available Speed Runs Quality Download
Q2_K 411 GB 8.0 GB — Won't run 68Good quality (B) · 68 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. GGUF · part 1 of 7 (opens in a new tab)
Q3_K_M 503 GB 8.0 GB — Won't run 81Great quality (A) · 81 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q4_K_M 626 GB 8.0 GB — Won't run 92Excellent quality (A+) · 92 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. GGUF (Q4_0) (opens in a new tab)
Q5_K_M 729 GB 8.0 GB — Won't run 94Excellent quality (A+) · 94 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q6_K 841 GB 8.0 GB — Won't run 96Excellent quality (A+) · 96 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q8_0 1,087 GB 8.0 GB — Won't run 97Excellent quality (A+) · 97 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
F16 2,050 GB 8.0 GB — Won't run 97Excellent quality (A+) · 97 of 100: how capable the model is at F16, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Hardware that can run it

Models that do run on the NVIDIA T1000 8GB

Quick answers

How much memory does MiMo V2.6 Pro (1T-A42B) need on the NVIDIA T1000 8GB?

Even at Q2_K it needs about 411 GB; the NVIDIA T1000 8GB has 8.0 GB usable.

What can the NVIDIA T1000 8GB run instead?

Nemotron 3.5 Bolt E4B, Nanbeige4.2 3B and K2 Horizon 7B run best on it; the page lists more, each with its speed.

What hardware can run MiMo V2.6 Pro (1T-A42B)?

M3 Ultra 512GB, AMD EPYC 7002 / 7003 series NAS 512GB and M5 Ultra 512GB run it; the page lists more, each with its speed.

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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