Model comparison
DeepSeek V4 Flash vs Qwen3 32B
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.8 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Qwen3 32B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Flash leads 53.7 to 19.6.
- The biggest single-benchmark swing is Chess Puzzles: 33% for DeepSeek V4 Flash and 5% for Qwen3 32B.
- DeepSeek V4 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 131K.
Side by side
| DeepSeek V4 Flash | Qwen3 32B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 53.6 | 38.8 |
| Released | 2026-04-24 | 2025-04 |
| Weights | Open | Open |
| Context window | 1M | 131K |
| Max output | 393K | 16K |
| Input $ / M tokens | $0.15 | $0.70 |
| Output $ / M tokens | $0.60 | $2.80 |
| Results tracked | 41 | 26 |
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Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.6 (#56), Qwen3 32B: 37.3 (#184)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| SciCode | 49.9% | 35.4% |
| LMArena Coding | 1457 | 1358 |
| FrontierCode | 18.8% | — |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1581 | — |
| WeirdML | 63% | — |
| ALE-Bench | 1,306 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Flash: —, Qwen3 32B: 32.3 (#58)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#25), Qwen3 32B: 19.6 (#233)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 52.2% | 54.9% |
| CritPt | 16.6% | 0.3% |
| Chess Puzzles | 33% | 5% |
| LMArena Hard Prompts | 1443 | 1335 |
| DTBench | 90.9% | 67.5% |
| LMCA | 41.7% | 17.3% |
| Epoch Capabilities Index | 154.51 | 138.51 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| Mystery Game Puzzles | 34% | — |
Math DeepSeek V4 Flash leads
DeepSeek V4 Flash: 60.0 (#31), Qwen3 32B: 37.9 (#89)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.4% | 66.9% |
| LMArena Math | 1427 | 1399 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| ProofBench | 56% | — |
Knowledge DeepSeek V4 Flash leads
DeepSeek V4 Flash: 55.5 (#43), Qwen3 32B: 40.0 (#112)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 91% | 65.7% |
| LMArena Expert | 1441 | 1362 |
| SimpleQA Verified | 33.6% | — |
| Vectara Hallucination Rate | — | 5.9% |
Multilingual DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.2 (#71), Qwen3 32B: 45.8 (#162)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1420 | 1317 |
| LMArena Chinese | 1467 | 1357 |
| LMArena German | 1418 | 1341 |
| LMArena Russian | 1428 | 1311 |
| LMArena French | 1438 | — |
| LMArena Japanese | 1403 | — |
| LMArena Korean | 1383 | — |
| LMArena Spanish | 1437 | — |
Instruction Following DeepSeek V4 Flash leads
DeepSeek V4 Flash: 75.1 (#76), Qwen3 32B: 69.1 (#174)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1421 | 1305 |
Long Context Too close to call
DeepSeek V4 Flash: 43.8 (#81), Qwen3 32B: 43.7 (#83)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1435 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference DeepSeek V4 Flash leads
DeepSeek V4 Flash: 64.0 (#59), Qwen3 32B: 53.1 (#158)
| Benchmark | DeepSeek V4 Flash | Qwen3 32B |
|---|---|---|
| LMArena Text | 1432 | 1340 |
| LMArena Creative Writing | 1403 | 1297 |
| LMArena Multi-Turn | 1449 | 1331 |
| EQ-Bench Creative Writing | 1559 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than Qwen3 32B?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.8 on the Noometry Index.
Which is cheaper, DeepSeek V4 Flash or Qwen3 32B?
DeepSeek V4 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.
Is DeepSeek V4 Flash or Qwen3 32B better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.6 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 32B share?
22 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Qwen3 32B has 26.