Model comparison
DeepSeek V4 Flash vs Qwen3 14B
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 35.5 on the Noometry Index.
Last verified . 9 shared benchmarks.
Summary
- They share 9 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 5 categories and Qwen3 14B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Flash leads 53.7 to 18.5.
- The biggest single-benchmark swing is Chess Puzzles: 33% for DeepSeek V4 Flash and 4% for Qwen3 14B.
- DeepSeek V4 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 131K.
Side by side
| DeepSeek V4 Flash | Qwen3 14B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 53.6 | 35.5 |
| Released | 2026-04-24 | 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 | 41 | 12 |
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Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.9 (#59), Qwen3 14B: 37.3 (#195)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| SciCode | 49.9% | 31.6% |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| WeirdML | 63% | — |
| LMArena Coding | 1457 | — |
| ALE-Bench | 1,306 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Flash: —, Qwen3 14B: 29.6 (#83)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#30), Qwen3 14B: 18.5 (#280)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 52.2% | 49.1% |
| CritPt | 16.6% | 0% |
| Chess Puzzles | 33% | 4% |
| DTBench | 90.9% | 64% |
| LMCA | 41.7% | 18.2% |
| Epoch Capabilities Index | 154.49 | 138.23 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| LMArena Hard Prompts | 1444 | — |
| Mystery Game Puzzles | 34% | — |
Math DeepSeek V4 Flash leads
DeepSeek V4 Flash: 60.3 (#37), Qwen3 14B: 38.6 (#133)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.4% | 66.4% |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| ProofBench | 56% | — |
| LMArena Math | 1427 | — |
Knowledge DeepSeek V4 Flash leads
DeepSeek V4 Flash: 55.4 (#48), Qwen3 14B: 39.3 (#134)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 91% | 63.8% |
| SimpleQA Verified | 33.6% | — |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1441 | — |
Multilingual Not comparable
DeepSeek V4 Flash: 53.0 (#72), Qwen3 14B: —
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1420 | — |
| LMArena Chinese | 1468 | — |
| LMArena French | 1439 | — |
| LMArena German | 1418 | — |
| LMArena Japanese | 1406 | — |
| LMArena Korean | 1384 | — |
| LMArena Russian | 1428 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
DeepSeek V4 Flash: 74.9 (#81), Qwen3 14B: —
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1421 | — |
Long Context DeepSeek V4 Flash leads
DeepSeek V4 Flash: 43.8 (#85), Qwen3 14B: 38.1 (#204)
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1434 | — |
Writing & Preference Not comparable
DeepSeek V4 Flash: 63.8 (#61), Qwen3 14B: —
| Benchmark | DeepSeek V4 Flash | Qwen3 14B |
|---|---|---|
| LMArena Text | 1432 | — |
| LMArena Creative Writing | 1403 | — |
| EQ-Bench Creative Writing | 1559 | — |
| LMArena Multi-Turn | 1449 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than Qwen3 14B?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 35.5 on the Noometry Index.
Which is cheaper, DeepSeek V4 Flash or Qwen3 14B?
DeepSeek V4 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 Flash or Qwen3 14B better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Flash does, with 1M tokens against 131K.
How many benchmarks do DeepSeek V4 Flash and Qwen3 14B share?
9 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Qwen3 14B has 12.