Model comparison
DeepSeek V4 Flash vs Qwen3-30B-A3B
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.9 on the Noometry Index.
Last verified . 28 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 28 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Qwen3-30B-A3B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Flash leads 53.7 to 22.2.
- The biggest single-benchmark swing is WeirdML: 63% for DeepSeek V4 Flash and 29.8% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4 Flash.
- DeepSeek V4 Flash accepts more context: 1M tokens versus 41K.
Side by side
| DeepSeek V4 Flash | Qwen3-30B-A3B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 53.6 | 38.9 |
| Released | 2026-04-24 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 1M | 41K |
| Max output | 393K | 16K |
| Input $ / M tokens | $0.15 | $0.12 |
| Output $ / M tokens | $0.60 | $0.50 |
| Results tracked | 41 | 32 |
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Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.9 (#59), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 49.9% | 33.3% |
| WeirdML | 63% | 29.8% |
| LMArena Coding | 1457 | 1416 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| ALE-Bench | 1,306 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Flash: —, Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#30), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 52.2% | 54.9% |
| CritPt | 16.6% | 0.3% |
| Chess Puzzles | 33% | 8% |
| LMArena Hard Prompts | 1444 | 1398 |
| DTBench | 90.9% | 69.3% |
| LMCA | 41.7% | 22.4% |
| Epoch Capabilities Index | 154.49 | 139.63 |
| 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: 60.3 (#37), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| MathArena Final-Answer Competitions | 76.5% | 47.8% |
| OTIS Mock AIME 2024-2025 | 94.4% | 70.3% |
| LMArena Math | 1427 | 1394 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| ProofBench | 56% | — |
Knowledge DeepSeek V4 Flash leads
DeepSeek V4 Flash: 55.4 (#48), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 91% | 70.1% |
| LMArena Expert | 1441 | 1396 |
| SimpleQA Verified | 33.6% | — |
| Confabulations | — | 12.3% |
Multilingual DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.0 (#72), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1420 | 1372 |
| LMArena Chinese | 1468 | 1433 |
| LMArena French | 1439 | 1418 |
| LMArena German | 1418 | 1380 |
| LMArena Japanese | 1406 | 1337 |
| LMArena Korean | 1384 | 1331 |
| LMArena Russian | 1428 | 1370 |
| LMArena Spanish | 1436 | 1404 |
Instruction Following DeepSeek V4 Flash leads
DeepSeek V4 Flash: 74.9 (#81), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1421 | 1363 |
Long Context DeepSeek V4 Flash leads
DeepSeek V4 Flash: 43.8 (#85), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1434 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference DeepSeek V4 Flash leads
DeepSeek V4 Flash: 63.8 (#61), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | DeepSeek V4 Flash | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1432 | 1384 |
| LMArena Creative Writing | 1403 | 1317 |
| LMArena Multi-Turn | 1449 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 1559 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than Qwen3-30B-A3B?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 38.9 on the Noometry Index.
Which is cheaper, DeepSeek V4 Flash or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; DeepSeek V4 Flash lists at $0.15 and $0.60.
Is DeepSeek V4 Flash or Qwen3-30B-A3B better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 37.5 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Flash does, with 1M tokens against 41K.
How many benchmarks do DeepSeek V4 Flash and Qwen3-30B-A3B share?
28 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Qwen3-30B-A3B has 32.