DeepSeek V4.1 Flash vs Qwen3 8
DeepSeek V4.1 Flash 
Qwen3 8 Verdict
- Qwen3 8 (max) leads on quality: 66.5 vs 61.9.
- DeepSeek V4.1 Flash (max) is stronger in coding, composite, long context.
- Qwen3 8 (max) is stronger in agents & tools, knowledge, multimodal, reasoning, human preference, maths.
- DeepSeek V4.1 Flash (max) is 10× cheaper ($0.262 vs $2.67 per 1M blended).
- DeepSeek V4.1 Flash (max) streams 5.6× faster (215 vs 39 tokens per second).
| Metric | DeepSeek V4.1 Flash (max) | Qwen3 8 (max) |
|---|---|---|
| BenchLeader Index | 61.9 | 66.5 |
| Agents & tools score | 59.6 | 68.3 |
| Coding score | 68.9 | 66.5 |
| Composite score | 74.5 | 74.3 |
| Knowledge score | 61.7 | 63.5 |
| Long context score | 68.5 | 66.6 |
| Multimodal score | 61.4 | 67.4 |
| Reasoning score | 69.5 | 76.3 |
| Human preference score | – | 68.2 |
| Maths score | – | 67.0 |
| Blended price $/M | $0.262 | $2.67 |
| Output speed | 215 tok/s | 39 tok/s |
| Time to first answer | 10.5 s | 55.1 s |
| Context window | 1M | 1M |
| SciCode | – | 52.9% |
| ProofBench | – | 58.0% |
| Epoch Capabilities Index | – | 156.6 |
| LMArena Text | – | 1481 |
| LMArena Hard Prompts | – | 1503 |
| LMArena Coding | – | 1522 |
| LMArena WebDev | 1614 | 1671 |
| LMArena Vision | – | 1315 |
| LMArena Agent | 4.9 | 3.3 |
| LiveBench | 81.1% | 78.5% |
| LiveBench Reasoning | 86.7% | 88.2% |
| LiveBench Coding | 80.0% | 72.9% |
| LiveBench Agentic Coding | 77.3% | 64.7% |
| LiveBench Mathematics | 93.3% | 91.3% |
| LiveBench Data Analysis | 79.3% | 78.4% |
| LiveBench Language | 81.2% | 79.7% |
| LiveBench Instruction Following | 70.0% | 74.1% |
| AA Intelligence Index | 39.5 | 45.4 |
| AA-LCR | 84.0% | 80.3% |
| MMMU-Pro | 77.0% | 82.8% |
| AA-Omniscience | -5.3 | 12.0 |
| GPQA Diamond (AA) | – | 92.8% |
| Humanity's Last Exam (AA) | 39.3% | 43.1% |
| SciCode (AA) | 51.9% | 53.2% |
| LiveCodeBench | – | 87.8% |
| MMLU-Pro | – | 88.6% |
| IOI | – | 68.9% |
| LegalBench | – | 83.6% |
| CorpFin | – | 65.8% |
| TaxEval | – | 75.5% |
| Terminal-Bench 2.1 (Vals) | – | 67.4% |
| SWE-bench (Vals) | – | 85.6% |
| GPQA Diamond (Vals) | – | 93.7% |
| Vals Index | – | 51.8 |
| CritPt | 14.3% | 20.0% |
| GDPval (AA) | 56.6% | 58.2% |
| τ²-Bench Banking (AA) | – | 51.3% |
| Code Migration | – | 24.0% |
| Excel Modeling Benchmark | – | 60.1% |
| Finance Agent v2 | – | 50.6% |
| Harvey's Legal Agent Benchmark | – | 10.4% |
| Legal Research Bench | – | 47.6% |
| MedCode | – | 40.7% |
| MedScribe | – | 85.0% |
| MMMU-Pro (Vals) | – | 88.0% |
| MortgageTax | – | 64.0% |
| MysteryMechanism | – | 23.9% |
| ProgramBench | – | 0.0% |
| Public Benefits Bench | – | 67.1% |
| SAGE | – | 51.3% |
| SkillsBench | – | 42.0% |
| Tax Agent Bench | – | 66.0% |
| Terminal-Bench 4.0 (Vals) | – | 24.8% |
| Terminal-Bench Science | – | 1.4% |
| Vals Multimodal Index | – | 65.4% |
| Vibe Code Bench 1-100 | – | 12.8% |
| Vibe Code Bench v1.1 | – | 64.7% |
| LMArena Maths | – | 1498 |
| LMArena Creative Writing | – | 1472 |
| LMArena Instruction Following | – | 1477 |
| LMArena Multi-turn | – | 1495 |
| LMArena Longer Queries | – | 1492 |
Data as of 2026-09-19. Best configuration of each model; every score links to its source on the model pages.
DeepSeek V4.1 Flash vs Qwen3 8: questions
- Is DeepSeek V4.1 Flash better than Qwen3 8?
- Qwen3 8 (max) leads on quality: 66.5 vs 61.9. The BenchLeader Index combines every independent quality benchmark; Qwen3 8 (max) is ahead overall as of 2026-09-19, but check the category scores for your use.
- Is DeepSeek V4.1 Flash better than Qwen3 8 for coding?
- DeepSeek V4.1 Flash scores higher in coding (69 vs 67 on the category index, where 50 is average).
- Is DeepSeek V4.1 Flash better than Qwen3 8 for agentic tasks?
- Qwen3 8 scores higher in agentic tasks (68 vs 60 on the category index, where 50 is average).
- Which is cheaper, DeepSeek V4.1 Flash or Qwen3 8?
- DeepSeek V4.1 Flash is cheaper: $0.262 against $2.67 per million tokens, blended at three input tokens per output token.
- Which is faster, DeepSeek V4.1 Flash or Qwen3 8?
- DeepSeek V4.1 Flash streams faster: 215 against 39 output tokens per second.
- Which has the larger context window?
- Both accept 1M tokens of context.