Mixtral 34Bx2 MoE 60B vs Mixtral 8x7B Instruct v0.1

Side-by-side comparison of VRAM requirements, quantization, context length, and hardware compatibility.

Mixtral 34Bx2 MoE 60B

cloudyu · 60.8B

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Mixtral 8x7B Instruct v0.1

Mistral AI · 46.7B

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Specifications

Mixtral 34Bx2 MoE 60BMixtral 8x7B Instruct v0.1
Parameters60.8B46.7B
Context200K33K
ArchitectureMixtralForCausalLMMixtralForCausalLM
LicenseApache 2.0Apache 2.0
Downloads8.2K881.0K
ReleasedJan 2026

VRAM by Quantization: Mixtral 34Bx2 MoE 60B vs Mixtral 8x7B Instruct v0.1

QuantizationBitsMixtral 34Bx2 MoE 60B VRAMMixtral 8x7B Instruct v0.1 VRAM
BF1616.00122.4 GB94.0 GB

Verdict

Mixtral 8x7B Instruct v0.1 needs less VRAM at BF16 (94.0 GB vs 122.4 GB), so it fits on smaller GPUs. Mixtral 34Bx2 MoE 60B supports a longer context window (200K tokens). Mixtral 8x7B Instruct v0.1 is the more widely downloaded of the two.

Frequently Asked Questions

Which needs less VRAM, Mixtral 34Bx2 MoE 60B or Mixtral 8x7B Instruct v0.1?

At BF16, Mixtral 34Bx2 MoE 60B needs 122.4 GB and Mixtral 8x7B Instruct v0.1 needs 94.0 GB, so Mixtral 8x7B Instruct v0.1 is the lighter option to run locally.

Which has a longer context window, Mixtral 34Bx2 MoE 60B or Mixtral 8x7B Instruct v0.1?

Mixtral 34Bx2 MoE 60B supports 200,000 tokens and Mixtral 8x7B Instruct v0.1 supports 32,768 tokens.

What is the difference between Mixtral 34Bx2 MoE 60B and Mixtral 8x7B Instruct v0.1?

Mixtral 34Bx2 MoE 60B is a 60.8B model from cloudyu (Mixtral family), while Mixtral 8x7B Instruct v0.1 is a 46.7B model from Mistral AI (Mixtral family). Compare their VRAM requirements above to see which fits your GPU or Mac.