Model comparison
DeepSeek V4 Pro vs Qwen2.5 14B Instruct
DeepSeek V4 Pro has enough public results to be ranked (#31); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in coding, where DeepSeek V4 Pro leads 52.4 to 37.7.
- Qwen2.5 14B Instruct is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 131K.
Side by side
| DeepSeek V4 Pro | Qwen2.5 14B Instruct | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 54.3 | 38.7 |
| Released | 2026-04-24 | 2024-09 |
| Weights | Open | Open |
| Context window | 1M | 131K |
| Max output | 393K | 8K |
| Input $ / M tokens | $0.66 | $0.35 |
| Output $ / M tokens | $1.98 | $1.40 |
| Results tracked | 48 | 3 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.4 (#34), Qwen2.5 14B Instruct: 37.7 (#191)
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| BigCodeBench Instruct | — | 39.8% |
| LMArena Coding | 1470 | — |
| BigCodeBench Complete | — | 52.2% |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.8 (#58), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning Not comparable
DeepSeek V4 Pro: 56.5 (#24), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| LMArena Hard Prompts | 1461 | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.31 | — |
| ForecastBench | 56.1 | — |
Math Not comparable
DeepSeek V4 Pro: 64.8 (#30), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| LMArena Math | 1455 | — |
Knowledge Not comparable
DeepSeek V4 Pro: 59.5 (#31), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |
| LMArena Expert | 1464 | — |
| MMLU | — | 79.9% |
Multilingual Not comparable
DeepSeek V4 Pro: 54.4 (#45), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Non-English | 1439 | — |
| LMArena Chinese | 1486 | — |
| LMArena French | 1472 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1445 | — |
| LMArena Korean | 1447 | — |
| LMArena Russian | 1453 | — |
| LMArena Spanish | 1458 | — |
Instruction Following Not comparable
DeepSeek V4 Pro: 76.1 (#47), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Instruction Following | 1448 | — |
Long Context Not comparable
DeepSeek V4 Pro: 45.0 (#51), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| CL-bench Life | 13.5% | — |
| LMArena Longer Query | 1458 | — |
Writing & Preference Not comparable
DeepSeek V4 Pro: 65.5 (#46), Qwen2.5 14B Instruct: —
| Benchmark | DeepSeek V4 Pro | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Text | 1451 | — |
| LMArena Creative Writing | 1446 | — |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |
| LMArena Multi-Turn | 1467 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than Qwen2.5 14B Instruct?
DeepSeek V4 Pro has enough public results to be ranked (#31); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Which is cheaper, DeepSeek V4 Pro or Qwen2.5 14B Instruct?
Qwen2.5 14B Instruct is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.
Is DeepSeek V4 Pro or Qwen2.5 14B Instruct better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 131K.
How many benchmarks do DeepSeek V4 Pro and Qwen2.5 14B Instruct share?
0 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Qwen2.5 14B Instruct has 3.