Verdict
DeepSeek-R1 leads 2–0 across 2 shared benchmarks.
DeepSeek-R1 2 · Mixtral 8x7B 0 · higher isn't always better — check the caveats below.
Reported scores — protocols may differ. How we compare
Vendor claims — compare against the measured scores above. A claim is what a developer says about its own model, not an independent measurement.
Reasoning
“After these steps, we obtained a checkpoint referred to as DeepSeek-R1, which achieves performance on par with OpenAI-o1-1217.”
“For education-oriented knowledge benchmarks such as MMLU, MMLU-Pro, and GPQA Diamond, DeepSeek-R1 demonstrates superior performance compared to DeepSeek-V3.”
Coding
“It shows strong performance in code generation.”
Context Handling
“It gracefully handles a context of 32k tokens.”
General
“It handles English, French, Italian, German and Spanish.”
Reasoning
“Mixtral matches or outperforms Llama 2 70B, as well as GPT3.5, on most benchmarks.”
Speed / Latency
“Mixtral outperforms Llama 2 70B on most benchmarks with 6x faster inference.”
DeepSeek-R1 leads 2–0 across 2 shared benchmarks. DeepSeek-R1 leads 2 benchmarks and Mixtral 8x7B leads 0. Higher isn't always better — see the integrity caveats on each benchmark.
DeepSeek-R1 and Mixtral 8x7B have 2 benchmarks in common in our data — those are the only rows where a direct, apples-to-apples comparison is drawn.