Model comparison
DeepSeek V4.1 Flash vs Qwen1.5-14B
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 32.1 on the Noometry Index.
Last verified . 14 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 14 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 8 categories and Qwen1.5-14B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek V4.1 Flash leads 65.8 to 33.7.
Side by side
| DeepSeek V4.1 Flash | Qwen1.5-14B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 50.3 | 32.1 |
| Released | 2026-09-09 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 25 | 17 |
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Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.8 (#29), Qwen1.5-14B: 32.5 (#259)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1511 | 1138 |
| LMArena WebDev | 1620 | — |
| SciCode | 51.9% | — |
| ALE-Bench | 1,092 | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 46.2 (#39), Qwen1.5-14B: 20.5 (#217)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1485 | 1113 |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Epoch Capabilities Index | 155.01 | — |
Math DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 48.4 (#52), Qwen1.5-14B: 29.9 (#214)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1493 | 1125 |
| ProofBench | 54% | — |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 41.6 (#97), Qwen1.5-14B: 29.3 (#230)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1505 | 1094 |
| MMLU | — | 68.6% |
Multilingual DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 55.5 (#29), Qwen1.5-14B: 30.8 (#257)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1452 | 1095 |
| LMArena Chinese | 1506 | 1147 |
| LMArena French | 1448 | 1115 |
| LMArena Russian | 1473 | 1046 |
| LMArena Spanish | 1499 | 1085 |
| LMArena German | — | 1043 |
| LMArena Japanese | — | 1019 |
Instruction Following DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 77.6 (#24), Qwen1.5-14B: 57.1 (#266)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1475 | 1102 |
Long Context DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 45.2 (#46), Qwen1.5-14B: 33.7 (#252)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1476 | 1113 |
Writing & Preference DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 65.8 (#43), Qwen1.5-14B: 33.7 (#270)
| Benchmark | DeepSeek V4.1 Flash | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1465 | 1128 |
| LMArena Creative Writing | 1436 | 1091 |
| LMArena Multi-Turn | 1460 | 1110 |
| EQ-Bench Creative Writing | 1540 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Qwen1.5-14B?
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 32.1 on the Noometry Index.
Is DeepSeek V4.1 Flash or Qwen1.5-14B better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.8 versus 32.5 in the Noometry coding category.
How many benchmarks do DeepSeek V4.1 Flash and Qwen1.5-14B share?
14 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Qwen1.5-14B has 17.