DeepSeek-R1 vs Qwen3 235B A22B
Wins 1 of 6 areas
Long documents
Wins 3 of 6 areas
Agents · Reasoning · Facts
Qwen3 235B A22B wins more areas, narrowly.DeepSeek-R1 is better at long documents.
Scores updated · 37 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- ReasoningHard problems that need careful thinking01Qwen3 235B A22B1 of 3 tests · 2 ties
- FactsGetting facts right instead of making them up12Qwen3 235B A22B2 of 3 tests
- AgentsCarrying out multi-step tasks on its own01Qwen3 235B A22B1 of 1 test
- Long documentsFinding answers in very long texts20DeepSeek-R12 of 2 tests
- CodingWriting and fixing software11Even1 each · 1 tie
- Following instructionsDoing exactly what it is asked00Even0 each · 2 ties
Agents rests on a single test.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
Qwen3 235B A22B costs 42% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where Qwen3 235B A22B pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+12.7points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+2.5points ahead
- Code for real scientific research problemsSciCode+1.6points ahead
Where DeepSeek-R1 pulls ahead
- Fixes real GitHub issues in Python projectsSWE-bench Verified+14.8points ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+12points ahead
- Questions about very long textsLongBench v2+8.2points ahead
Every test, side by side
All 37 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingEven
- SWE-bench VerifiedDeepSeek-R1 by 14.849.234.4+14.8
- SciCodeQwen3 235B A22B by 1.638.339.9+1.6
- Terminal-Bench Hardtie6.16.1tie
ReasoningQwen3 235B A22B
- Humanity's Last ExamQwen3 235B A22B by 2.58.511+2.5
- GPQA Diamondtie70.870tie
- CritPttie0.60tie
FactsQwen3 235B A22B
- AA-Omniscience · Non-hallucinationQwen3 235B A22B by 12.79.722.4+12.7
- AA-Omniscience · AccuracyDeepSeek-R1 by 1230.518.5+12
- Vectara HHEM hallucination ratelower is betterQwen3 235B A22B by 211.39.3+2
Long documentsDeepSeek-R1
- AA-LCRDeepSeek-R1 by 57.757.70+57.7
- LongBench v2DeepSeek-R1 by 8.258.350.1+8.2
Following instructionsEven
- Multi-Challengetie40.741.2tie
- IFBenchtie3938.7tie
Other results23 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- ZebraLogicDeepSeek-R1 by 4178.737.7+41
- CNMO 2024DeepSeek-R1 by 30.278.848.6+30.2
- HMMT Feb. 2025Qwen3 235B A22B by 20.841.762.5+20.8
- SimpleQADeepSeek-R1 by 16.930.113.2+16.9
- MMLU-ProDeepSeek-R1 by 15.88468.2+15.8
- τ²-Bench Telecom (AA run)Qwen3 235B A22B by 12.611.424+12.6
- AA-OmniscienceDeepSeek-R1 by 12.5-32.2-44.7+12.5
- AIME 2025Qwen3 235B A22B by 11.57081.5+11.5
- LiveCodeBench (24/8~25/5)Qwen3 235B A22B by 1055.965.9+10
- MMLU-ProXDeepSeek-R1 by 8.875.566.7+8.8
- OpenAI-MRCR (128k)DeepSeek-R1 by 8.135.827.7+8.1
- Artificial Analysis Coding IndexDeepSeek-R1 by 7.224.617.4+7.2
- FullStackBenchDeepSeek-R1 by 7.270.162.9+7.2
- LiveCodeBenchQwen3 235B A22B by 7.263.570.7+7.2
- MATH-500 (EM)DeepSeek-R1 by 6.197.391.2+6.1
- AIME 2024Qwen3 235B A22B by 5.979.885.7+5.9
- MMLU-ReduxDeepSeek-R1 by 5.592.987.4+5.5
- MMLUDeepSeek-R1 by 3.890.887+3.8
- vectara_answer_rateDeepSeek-R1 by 2.19794.9+2.1
- vectara_factual_consistencyQwen3 235B A22B by 288.790.7+2
- AA IntelligenceDeepSeek-R1 by 1.911.49.5+1.9
- vectara_avg_summary_lengthQwen3 235B A22B by 12.1 rating points93.5105.6+12.1 rating
- IFEvaltie83.383.2tie
Questions people ask
Which is better, DeepSeek-R1 or Qwen3 235B A22B?
Qwen3 235B A22B wins three of the six areas where both have results: agents, reasoning and facts. DeepSeek-R1 wins long documents. They are level on coding and following instructions.
Which is better for coding?
Neither. They win 1 coding test each of the 3 both models report, and 1 is a tie.
Which is cheaper?
DeepSeek-R1 costs $2.00 per million input tokens and $4.00 per million output tokens; Qwen3 235B A22B costs $0.70 and $2.80. That makes Qwen3 235B A22B about 42% cheaper for the same work.
How do you compare the two?
We use the 37 benchmark tests both models have published scores on. The verdict counts the 14 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 23 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.