Can RTX 4070 12GB run Mixtral-8x7B-Instruct-v0.1?

NVIDIA · 12 GB GDDR6X · 504 GB/s bandwidth · Mistral · 46.7B (active 12.9B) · MoE · model ctx up to 32K

No — Mixtral-8x7B-Instruct-v0.1 at Q4 needs ≈ 27.98 GB even at 4K context, beyond the RTX 4070 12GB's 12 GB GDDR6X. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 11.9 tok/s (estimated, batch 1). FP16 needs ≈ 96.98 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

Quant	Context	VRAM needed	Fits?	tok/s (decode)
Q4	4K	27.98 GB	No	13.1 est.
Q4	8K default	29.27 GB	No	11.9 est.
Q4	32K	37.01 GB	No	7.5 est.
FP16	4K	95.69 GB	No	—
FP16	8K default	96.98 GB	No	—
FP16	32K	104.72 GB	No	—

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

Quant	Weights	KV cache	Overhead	Total needed	RTX 4070 12GB VRAM
Q4	25.69 GB	2.58 GB	1 GB	29.27 GB	12 GB
FP16	93.4 GB	2.58 GB	1 GB	96.98 GB	12 GB

Other GPUs that run Mixtral-8x7B-Instruct-v0.1

• B200 192GB SXM — ≈394.6 tok/s Q4 est.
• MI300X 192GB — ≈261.5 tok/s Q4 est.
• H200 141GB SXM5 — ≈236.8 tok/s Q4 est.
• H100 80GB SXM5 — ≈165.3 tok/s Q4 est.
• Gaudi 3 128GB — ≈161.6 tok/s Q4 est.
• A100 80GB SXM4 — ≈100.6 tok/s Q4 est.
• RTX 5090 32GB — ≈88.4 tok/s Q4 est.
• RTX 6000 Ada 48GB — ≈47.4 tok/s Q4 est.

All GPUs for Mixtral-8x7B-Instruct-v0.1 →

Other models for the RTX 4070 12GB

• Qwen3-0.6B — ≈400.9 tok/s Q4 est.
• gemma-3-1b-it — ≈320.7 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈267.3 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈160.7 tok/s Q4 measured
• Qwen3-1.7B — ≈160.4 tok/s Q4 est.
• Phi-4-mini-instruct — ≈84.4 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈84.4 tok/s Q4 est.
• gemma-3-4b-it — ≈82.2 tok/s Q4 est.

All models on the RTX 4070 12GB →