DeepSeek-R1 vs Qwen3 14B
Wins 3 of 6 areas
Coding · Reasoning · Long documents
Wins 2 of 6 areas
Facts · Following instructions
DeepSeek-R1 wins more areas, narrowly.Qwen3 14B is cheaper and better at facts.
Scores updated · 28 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.
- CodingWriting and fixing software30DeepSeek-R13 of 3 tests
- ReasoningHard problems that need careful thinking20DeepSeek-R12 of 3 tests · 1 tie
- Long documentsFinding answers in very long texts10DeepSeek-R11 of 1 test
- FactsGetting facts right instead of making them up12Qwen3 14B2 of 3 tests
- Following instructionsDoing exactly what it is asked01Qwen3 14B1 of 1 test
- AgentsCarrying out multi-step tasks on its own00Even0 each · 3 ties
Long documents and following instructions rest on a single test each.
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 14B costs 71% less for the same work.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where DeepSeek-R1 pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+15.2points ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+14.2points ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+10.4points ahead
Where Qwen3 14B pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+14.5points ahead
- Follows unfamiliar, precisely checkable instructionsIFBench+1.5points ahead
Every test, side by side
All 28 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-R1
- Terminal-Bench 2.1DeepSeek-R1 by 14.219.14.9+14.2
- SciCodeDeepSeek-R1 by 7.638.330.7+7.6
- Terminal-Bench HardDeepSeek-R1 by 2.36.13.8+2.3
AgentsEven
- τ-Bench V3 · Bankingtie6.45.6tie
- GDPValtie00tie
- Terminal-Bench 4.0tie00tie
ReasoningDeepSeek-R1
- GPQA DiamondDeepSeek-R1 by 10.470.860.4+10.4
- Humanity's Last ExamDeepSeek-R1 by 48.54.5+4
- CritPttie0.60tie
FactsQwen3 14B
- AA-Omniscience · AccuracyDeepSeek-R1 by 15.230.515.3+15.2
- AA-Omniscience · Non-hallucinationQwen3 14B by 14.59.724.2+14.5
- Vectara HHEM hallucination ratelower is betterQwen3 14B by 5.911.35.4+5.9
Other results14 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.
- τ²-Bench Telecom (AA run)Qwen3 14B by 23.111.434.5+23.1
- AA-OmniscienceDeepSeek-R1 by 16.7-32.2-49+16.7
- Artificial Analysis Coding IndexDeepSeek-R1 by 10.824.613.8+10.8
- ZebraLogicQwen3 14B by 9.878.788.5+9.8
- vectara_factual_consistencyQwen3 14B by 5.988.794.6+5.9
- C-EvalDeepSeek-R1 by 5.691.886.2+5.6
- MMLU-ReduxDeepSeek-R1 by 4.392.988.6+4.3
- LiveCodeBenchDeepSeek-R1 by 4.263.559.3+4.2
- AIME 2024Qwen3 14B by 3.979.883.7+3.9
- AA IntelligenceDeepSeek-R1 by 3.211.48.2+3.2
- vectara_answer_rateQwen3 14B by 2.99799.9+2.9
- vectara_avg_summary_lengthQwen3 14B by 17.6 rating points93.5111.1+17.6 rating
- MATH-500 (EM)tie97.396.8tie
- AIME 2025tie7070.4tie
Questions people ask
Which is better, DeepSeek-R1 or Qwen3 14B?
DeepSeek-R1 wins three of the six areas where both have results: coding, reasoning and long documents. Qwen3 14B wins facts and following instructions, and costs 71% less. They are level on agents.
Which is better for coding?
DeepSeek-R1. It wins 3 of the 3 coding tests both models report; Qwen3 14B wins none.
Which is cheaper?
DeepSeek-R1 costs $2.00 per million input tokens and $4.00 per million output tokens; Qwen3 14B costs $0.35 and $1.40. That makes Qwen3 14B about 71% cheaper for the same work.
How do you compare the two?
We use the 28 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 14 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.