Model comparison
DeepSeek V4.1 Flash vs Qwen3 14B
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 35.5 on the Noometry Index.
Last verified . 7 shared benchmarks.
Summary
- They share 7 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 6 categories and Qwen3 14B in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4.1 Flash leads 50.2 to 18.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for DeepSeek V4.1 Flash and 66.4% for Qwen3 14B.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 131K.
Side by side
| DeepSeek V4.1 Flash | Qwen3 14B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 52.8 | 35.5 |
| Released | 2026-09-09 | 2025-04 |
| Weights | Open | Open |
| Context window | 1M | 131K |
| Max output | 393K | 8K |
| Input $ / M tokens | $0.15 | $0.35 |
| Output $ / M tokens | $0.60 | $1.40 |
| Results tracked | 37 | 12 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.9 (#32), Qwen3 14B: 37.3 (#195)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| SciCode | 51.9% | 31.6% |
| LMArena WebDev | 1619 | — |
| LMArena Coding | 1506 | — |
| ALE-Bench | 1,092 | — |
Agentic & Tool Use DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 31.2 (#69), Qwen3 14B: 29.6 (#83)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| APEX-Agents | 39.5% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
| GDP.pdf | 19.8% | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 50.2 (#36), Qwen3 14B: 18.5 (#280)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| CritPt | 14.3% | 0% |
| DTBench | 89.9% | 64% |
| LMCA | 47% | 18.2% |
| Epoch Capabilities Index | 154.9 | 138.23 |
| Kagi LLM Benchmark | — | 49.1% |
| NYT Connections (extended) | 89.6% | — |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1483 | — |
| Mystery Game Puzzles | 43% | — |
| Surface Evolver Bench | 46.3% | — |
Math DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 66.7 (#25), Qwen3 14B: 38.6 (#133)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.3% | 66.4% |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 26.8% | — |
| ProofBench | 54% | — |
| LMArena Math | 1477 | — |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 57.9 (#38), Qwen3 14B: 39.3 (#134)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 89.8% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1506 | — |
Multimodal Not comparable
DeepSeek V4.1 Flash: 39.1 (#61), Qwen3 14B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1277 | — |
| Furniture Assembly | 34.2% | — |
Multilingual Not comparable
DeepSeek V4.1 Flash: 55.0 (#35), Qwen3 14B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1448 | — |
| LMArena Chinese | 1497 | — |
| LMArena French | 1452 | — |
| LMArena German | 1484 | — |
| LMArena Japanese | 1412 | — |
| LMArena Korean | 1452 | — |
| LMArena Russian | 1471 | — |
| LMArena Spanish | 1459 | — |
Instruction Following Not comparable
DeepSeek V4.1 Flash: 77.3 (#26), Qwen3 14B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1474 | — |
Long Context DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 45.2 (#47), Qwen3 14B: 38.1 (#204)
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1475 | — |
Writing & Preference Not comparable
DeepSeek V4.1 Flash: 65.4 (#48), Qwen3 14B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3 14B |
|---|---|---|
| LMArena Text | 1462 | — |
| LMArena Creative Writing | 1435 | — |
| EQ-Bench Creative Writing | 1540 | — |
| LMArena Multi-Turn | 1457 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Qwen3 14B?
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 35.5 on the Noometry Index.
Which is cheaper, DeepSeek V4.1 Flash or Qwen3 14B?
DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is DeepSeek V4.1 Flash or Qwen3 14B better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4.1 Flash does, with 1M tokens against 131K.
How many benchmarks do DeepSeek V4.1 Flash and Qwen3 14B share?
7 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Qwen3 14B has 12.