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Mistral Nemo vs Qwen3.7 Max

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Mistral Nemo and Qwen3.7 Max.

Mistral

Mistral Nemo

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

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Alibaba

Qwen3.7 Max

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...

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Technical Specifications

SpecificationMistral NemoQwen3.7 Max
ProviderMistralAlibaba
Context Window131,072 tokens1,000,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostableself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2024-07-192026-05-21

API Pricing Comparison

Input Price per Million Tokens

Mistral Nemo

$0.02

Qwen3.7 Max

$1.25

Output Price per Million Tokens

Mistral Nemo

$0.03

Qwen3.7 Max

$3.75

Want to test both models live?

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Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs9150.0%
Mistral Nemo
Qwen3.7 Max
HumanEvalPython coding & logic synthesis
N/Avs9580.0%
Mistral Nemo
Qwen3.7 Max
MATHComplex mathematical problem solving
N/Avs8820.0%
Mistral Nemo
Qwen3.7 Max
GPQAGraduate-level expert reasoning
N/Avs6050.0%
Mistral Nemo
Qwen3.7 Max
HellaSwagCommonsense reasoning and inference
N/Avs9100.0%
Mistral Nemo
Qwen3.7 Max
MT-BenchMulti-turn conversation flow quality
N/Avs940.0%
Mistral Nemo
Qwen3.7 Max

Mistral Nemo Quirks & Gotchas

No developer gotchas reported.

Qwen3.7 Max Quirks & Gotchas

No developer gotchas reported.