For all our models, the maximum generation length is set to 32,768 tokens. For benchmarks requiring sampling, we use a temperature of $0.6$, a top-p value of $0.95$, and generate 64 responses per query to estimate pass@1.

To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen. DeepSeek-R1-Distill-Qwen-32B outperforms OpenAI-o1-mini across various benchmarks, ...

October 13, 2025 - For engineering-related tasks, ... achieves outstanding results, significantly outperforming DeepSeek-V3 with scores of 90.8% on MMLU, 84.0% on MMLU-Pro, and 71.5% on GPQA Diamond....

... Temperature: 0.6. Top-p value: 0.95. Pass@1 estimation: Generated 64 responses per query. ... DeepSeek R1 outperformed o1, Claude 3.5 Sonnet and other models in the majority of reasoning benchmarks

May 30, 2025 - Improvements are also dramatic in coding benchmarks. On the Codeforces programming challenge, R1–0528’s rating is about 1930, up from ~1530 before- a ~400-point leap that reflects far better code generation and problem-solving.

June 4, 2025 - DeepSeek-R1 performs strongly with a score of 49.2%, slightly ahead of OpenAI o1-1217’s 48.9%. This result positions DeepSeek-R1 as a strong contender in specialized reasoning tasks like software verification.

According to the same benchmark, ... and coding performance, it has a score of 96.3 in the Codeforce benchmark, 71.5 in the GPQA-diamond benchmark, and 97.3 in the MATH-500 benchmark....

Analysis of DeepSeek's DeepSeek R1 0528 (May '25) and comparison to other AI models across key metrics including quality, price, performance (tokens per second & time to first token), context window & more.

Reasoning Tasks: Shows performance on par with OpenAI’s o1 model across complex reasoning benchmarks. Image source: DeepSeek R1 Research Paper (Modified)

DeepSeek : Speed: 24.34 tokens/s, Total: 424 tokens, Prompt: 12 tokens, Completion: 412 tokens, Time: 16.93s, Latency: 1.11s, Length: 1904 chars Fireworks : Speed: 21.41 tokens/s, Total: 373 tokens, Prompt: 10 tokens, Completion: 363 tokens, ...

Accuracy · 69.64% Latency · 77.95s · Cost (In/Out) 1.35 / 5.4 · Context Window · 164k · Max Output Tokens · 164k · Input Modality · Benchmarks · Accuracy · Rankings · CaseLaw (v2) 0.0% 57/ 57 ·

May 29, 2025 - AIME 2024, surpassing Qwen3 8B by +10.0% and matching the performance of Qwen3-235B-thinking. We believe that the chain-of-thought from DeepSeek-R1-0528 will hold significant importance for both academic research on reasoning models and industrial ...

This model achieves state-of-the-art (SOTA) performance among open-source models on the AIME 2024, surpassing Qwen3 8B by +10.0% and matching the performance of Qwen3-235B-thinking.

April 24, 2025 - Set up and run the GPQA-Diamond benchmark on DeepSeek-R1's distilled models locally to evaluate its reasoning capabilities.

Last week, DeepSeek published their new R1-Zero and R1 “reasoner” systems that is competitive with OpenAI’s o1 system on ARC-AGI-1. R1-Zero, R1, and o1 (low compute) all score around 15-20% – in contrast to GPT-4o’s 5%, the pinnacle ...

In this update, DeepSeek R1 has significantly improved its reasoning and inference capabilities. The model has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic.

Longer Reasoning, Better Performance. DeepSeek-R1-Lite-Preview shows steady score improvements on AIME as thought length increases.

In this update, DeepSeek R1 has significantly improved its reasoning and inference capabilities. The model has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic.

April 4, 2025 - Benchmark Excellence: R1 matches OpenAI o1 in key tasks, with some areas of clear outperformance. While DeepSeek R1 builds upon the collective work of open-source research, its efficiency and performance demonstrate how creativity and strategic ...

January 28, 2025 - SWE-bench Verified Benchmark: O3 scored 71.7%, surpassing DeepSeek R1 (49.2%) and OpenAI's O1 (48.9%).