Model comparison
DeepSeek V4 Flash vs Qwen1.5 4b Chat
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 28.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Qwen1.5 4b Chat in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek V4 Flash leads 63.8 to 23.8.
Side by side
| DeepSeek V4 Flash | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 53.6 | 28.8 |
| Released | 2026-04-24 | — |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 41 | 13 |
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Category by category
Coding DeepSeek V4 Flash leads
DeepSeek V4 Flash: 47.9 (#59), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1457 | 999 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 49.9% | — |
| WeirdML | 63% | — |
| ALE-Bench | 1,306 | — |
Reasoning DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.7 (#30), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1444 | 976 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| CritPt | 16.6% | — |
| Chess Puzzles | 33% | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 90.9% | — |
| LMCA | 41.7% | — |
| Epoch Capabilities Index | 154.49 | — |
Math DeepSeek V4 Flash leads
DeepSeek V4 Flash: 60.3 (#37), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1427 | 1026 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| OTIS Mock AIME 2024-2025 | 94.4% | — |
| ProofBench | 56% | — |
Knowledge DeepSeek V4 Flash leads
DeepSeek V4 Flash: 55.4 (#48), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1441 | 980 |
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 33.6% | — |
Multilingual DeepSeek V4 Flash leads
DeepSeek V4 Flash: 53.0 (#72), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1420 | 979 |
| LMArena Chinese | 1468 | 1024 |
| LMArena German | 1418 | 902 |
| LMArena Russian | 1428 | 952 |
| LMArena French | 1439 | — |
| LMArena Japanese | 1406 | — |
| LMArena Korean | 1384 | — |
| LMArena Spanish | 1436 | — |
Instruction Following DeepSeek V4 Flash leads
DeepSeek V4 Flash: 74.9 (#81), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1421 | 978 |
Long Context DeepSeek V4 Flash leads
DeepSeek V4 Flash: 43.8 (#85), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1434 | 988 |
Writing & Preference DeepSeek V4 Flash leads
DeepSeek V4 Flash: 63.8 (#61), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | DeepSeek V4 Flash | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1432 | 997 |
| LMArena Creative Writing | 1403 | 969 |
| LMArena Multi-Turn | 1449 | 977 |
| EQ-Bench Creative Writing | 1559 | — |
Frequently asked questions
Is DeepSeek V4 Flash better than Qwen1.5 4b Chat?
DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 28.8 on the Noometry Index.
Is DeepSeek V4 Flash or Qwen1.5 4b Chat better for coding?
DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 29.1 in the Noometry coding category.
How many benchmarks do DeepSeek V4 Flash and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Qwen1.5 4b Chat has 13.