DeepSeekDeepSeek V4 ProVSMistral AIMixtral 8x7B v0.1
Our Take
Standardized reasoning and coding benchmarks are currently pending verification for one or both of these models. We recommend testing DeepSeek V4 Pro and Mixtral 8x7B v0.1 directly in their respective provider playgrounds to see which fits your specific prompt styles best.
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-pro)
52.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
88%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.17Input: $1.74 | Output: $3.48Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (human-eval)
40.2%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
N/Agraduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
32.77k tokensFrequently Asked Questions about DeepSeek V4 Pro vs Mixtral 8x7B v0.1
For coding tasks, DeepSeek V4 Pro scores 52.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while Mixtral 8x7B v0.1 scores 40.2% on human-eval (basic standalone code completion and simple functions).
Related Matchups
Explore similar comparisons for DeepSeek V4 Pro and Mixtral 8x7B v0.1.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.