Model comparison
Gemini 2.5 Flash vs Qwen3 Coder Next
Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 2.9× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Google
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 0 categories and Qwen3 Coder Next in 2 categories; one gap is clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3 Coder Next leads 22.4 to 18.1.
- The biggest single-benchmark swing is WeirdML: 41.9% for Gemini 2.5 Flash and 34.4% for Qwen3 Coder Next.
- Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
- Gemini 2.5 Flash 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 Flash | Qwen3 Coder Next | |
|---|---|---|
| Provider | Alibaba (Qwen) | |
| Noometry Index | 39.3 | 34.3 |
| Released | 2025-04-17 | 2026-02-02 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.30 | $0.12 |
| Output $ / M tokens | $2.50 | $0.80 |
| Results tracked | 54 | 3 |
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Category by category
Coding Too close to call
Gemini 2.5 Flash: 35.8 (#220), Qwen3 Coder Next: 36.3 (#210)
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| WeirdML | 41.9% | 34.4% |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| SciCode | — | 32.3% |
| LMArena Coding | 1424 | — |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Not comparable
Gemini 2.5 Flash: 30.8 (#74), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Qwen3 Coder Next leads
Gemini 2.5 Flash: 18.1 (#286), Qwen3 Coder Next: 22.4 (#196)
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| CritPt | 1.1% | 0% |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| EnigmaEval | 2.7% | — |
| LMArena Hard Prompts | 1422 | — |
| DTBench | 76.5% | — |
| LMCA | 27.5% | — |
| Epoch Capabilities Index | 143.03 | — |
| ForecastBench | 60.6 | — |
Math Not comparable
Gemini 2.5 Flash: 39.9 (#98), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| Omni-MATH | 38.5% | — |
| LMArena Math | 1415 | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Gemini 2.5 Flash: 36.4 (#168), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| Vectara Hallucination Rate | 7.8% | — |
| GPQA (HELM) | 39% | — |
| LMArena Expert | 1426 | — |
Multimodal Not comparable
Gemini 2.5 Flash: 41.8 (#32), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| LMArena Vision | 1253 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Not comparable
Gemini 2.5 Flash: 52.3 (#88), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| LMArena Non-English | 1409 | — |
| LMArena Chinese | 1450 | — |
| LMArena French | 1433 | — |
| LMArena German | 1418 | — |
| LMArena Japanese | 1405 | — |
| LMArena Korean | 1385 | — |
| LMArena Russian | 1415 | — |
| LMArena Spanish | 1421 | — |
Instruction Following Not comparable
Gemini 2.5 Flash: 75.7 (#54), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| IFEval | 89.8% | — |
| LMArena Instruction Following | 1405 | — |
Long Context Not comparable
Gemini 2.5 Flash: 47.5 (#17), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| Fiction.LiveBench | 77.8% | — |
| LMArena Longer Query | 1419 | — |
Writing & Preference Not comparable
Gemini 2.5 Flash: 53.8 (#157), Qwen3 Coder Next: —
| Benchmark | Gemini 2.5 Flash | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1417 | — |
| LMArena Creative Writing | 1400 | — |
| Short-Story Creative Writing | 76.5% | — |
| EQ-Bench Creative Writing | 1137 | — |
| WildBench | 81.7% | — |
| LMArena Multi-Turn | 1408 | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Qwen3 Coder Next?
Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 34.3 on the Noometry Index. Qwen3 Coder Next costs 2.9× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash 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 Flash lists at $0.30 and $2.50.
Is Gemini 2.5 Flash or Qwen3 Coder Next better for coding?
They score almost the same on coding (35.8 vs 36.3); test both on your own repository before choosing.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 262K.
How many benchmarks do Gemini 2.5 Flash and Qwen3 Coder Next share?
2 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen3 Coder Next has 3.