Model comparison
DeepSeek V4.1 Flash vs Qwen3-1.7B
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 26.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in math, where DeepSeek V4.1 Flash leads 48.4 to 15.4.
Side by side
| DeepSeek V4.1 Flash | Qwen3-1.7B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 50.3 | 26.2 |
| Released | 2026-09-09 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.60 | — |
| Results tracked | 25 | 4 |
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Category by category
Coding Not comparable
DeepSeek V4.1 Flash: 52.8 (#29), Qwen3-1.7B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| LMArena WebDev | 1620 | — |
| SciCode | 51.9% | — |
| LMArena Coding | 1511 | — |
| ALE-Bench | 1,092 | — |
Agentic & Tool Use Not comparable
DeepSeek V4.1 Flash: —, Qwen3-1.7B: 24.5 (#108)
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 46.2 (#39), Qwen3-1.7B: 18.5 (#263)
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1485 | — |
| 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), Qwen3-1.7B: 15.4 (#288)
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| ProofBench | 54% | — |
| LMArena Math | 1493 | — |
Knowledge DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 41.6 (#97), Qwen3-1.7B: 19.6 (#273)
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | — | 38% |
| LMArena Expert | 1505 | — |
Multilingual Not comparable
DeepSeek V4.1 Flash: 55.5 (#29), Qwen3-1.7B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1452 | — |
| LMArena Chinese | 1506 | — |
| LMArena French | 1448 | — |
| LMArena Russian | 1473 | — |
| LMArena Spanish | 1499 | — |
Instruction Following Not comparable
DeepSeek V4.1 Flash: 77.6 (#24), Qwen3-1.7B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1475 | — |
Long Context Not comparable
DeepSeek V4.1 Flash: 45.2 (#46), Qwen3-1.7B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1476 | — |
Writing & Preference Not comparable
DeepSeek V4.1 Flash: 65.8 (#43), Qwen3-1.7B: —
| Benchmark | DeepSeek V4.1 Flash | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1465 | — |
| LMArena Creative Writing | 1436 | — |
| EQ-Bench Creative Writing | 1540 | — |
| LMArena Multi-Turn | 1460 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Qwen3-1.7B?
DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 26.2 on the Noometry Index.
How many benchmarks do DeepSeek V4.1 Flash and Qwen3-1.7B share?
0 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Qwen3-1.7B has 4.