Model comparison
Gemini 2.5 Pro vs Qwen3 Coder Next
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 12× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 2 categories and Qwen3 Coder Next in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 2.5 Pro leads 28.8 to 22.4.
- The biggest single-benchmark swing is WeirdML: 54% for Gemini 2.5 Pro and 34.4% for Qwen3 Coder Next.
- Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 262K.
- Qwen3 Coder Next has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Pro | Qwen3 Coder Next | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 45.0 | 34.3 |
| Released | 2025-03-25 | 2026-02-02 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $1.25 | $0.12 |
| Output $ / M tokens | $10 | $0.80 |
| Results tracked | 78 | 3 |
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Category by category
Coding Gemini 2.5 Pro leads
Gemini 2.5 Pro: 42.4 (#101), Qwen3 Coder Next: 36.3 (#210)
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| SciCode | 42.8% | 32.3% |
| WeirdML | 54% | 34.4% |
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| LMArena WebDev | 1227 | — |
| GSO | 3.9% | — |
| LiveBench Coding | 85.9% | — |
| LMArena Coding | 1452 | — |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Pro: 29.2 (#88), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |
Reasoning Gemini 2.5 Pro leads
Gemini 2.5 Pro: 28.8 (#99), Qwen3 Coder Next: 22.4 (#196)
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| CritPt | 2% | 0% |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LMArena Hard Prompts | 1455 | — |
| DTBench | 82.4% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| Epoch Capabilities Index | 145.32 | — |
| ForecastBench | 61.3 | — |
| LiveBench | 82.3% | — |
Math Not comparable
Gemini 2.5 Pro: 32.5 (#213), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 84.7% | — |
| Omni-MATH | 41.6% | — |
| LiveBench Math | 90.2% | — |
| LMArena Math | 1450 | — |
| MATH Level 5 | 95.9% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Gemini 2.5 Pro: 56.0 (#46), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| GPQA Diamond | 85.3% | — |
| Humanity's Last Exam | 21.6% | — |
| MMLU-Pro | 86.3% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| GPQA (HELM) | 74.9% | — |
| LMArena Expert | 1452 | — |
Multimodal Not comparable
Gemini 2.5 Pro: 45.2 (#18), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |
Multilingual Not comparable
Gemini 2.5 Pro: 55.3 (#31), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| LMArena Non-English | 1451 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1472 | — |
| LMArena German | 1487 | — |
| LMArena Japanese | 1461 | — |
| LMArena Korean | 1434 | — |
| LMArena Russian | 1461 | — |
| LMArena Spanish | 1473 | — |
Instruction Following Not comparable
Gemini 2.5 Pro: 75.0 (#75), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| LiveBench Instruction Following | 80.6% | — |
| IFEval | 84% | — |
| LMArena Instruction Following | 1437 | — |
Long Context Not comparable
Gemini 2.5 Pro: 59.8 (#5), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| Fiction.LiveBench | 91.7% | — |
| LMArena Longer Query | 1449 | — |
Writing & Preference Not comparable
Gemini 2.5 Pro: 63.7 (#62), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Pro | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1458 | — |
| LMArena Creative Writing | 1454 | — |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| WildBench | 85.7% | — |
| LMArena Multi-Turn | 1453 | — |
| LiveBench Language | 67.8% | — |
Frequently asked questions
Is Gemini 2.5 Pro better than Qwen3 Coder Next?
Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 12× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Pro or Qwen3 Coder Next?
Qwen3 Coder Next is cheaper. It lists at $0.12 per million input tokens and $0.80 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.
Is Gemini 2.5 Pro or Qwen3 Coder Next better for coding?
Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 36.3 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Pro does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Pro and Qwen3 Coder Next share?
3 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and Qwen3 Coder Next has 3.