Model comparison
Gemini 2.5 Flash vs Kimi K2.7 Code
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 39.3 on the Noometry Index. Gemini 2.5 Flash costs 2.0× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
GoogleSummary
- They share 7 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 1 category and Kimi K2.7 Code in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 18.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.1% for Gemini 2.5 Flash and 95.6% for Kimi K2.7 Code.
- Gemini 2.5 Flash is cheaper at $0.30 / $2.50 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Kimi K2.7 Code has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Kimi K2.7 Code | |
|---|---|---|
| Provider | Moonshot AI | |
| Noometry Index | 39.3 | 43.3 |
| Released | 2025-04-17 | 2026-06-12 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 66K | 262K |
| Input $ / M tokens | $0.30 | $0.95 |
| Output $ / M tokens | $2.50 | $4 |
| Results tracked | 54 | 19 |
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Category by category
Coding Kimi K2.7 Code leads
Gemini 2.5 Flash: 35.8 (#220), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| WeirdML | 41.9% | 54.1% |
| ALE-Bench | 661.88 | 886.23 |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1473 |
| SciCode | — | 47.5% |
| LMArena Coding | 1424 | — |
Agentic & Tool Use Gemini 2.5 Flash leads
Gemini 2.5 Flash: 30.8 (#74), Kimi K2.7 Code: 24.0 (#122)
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| Vending-Bench 2 | 548.84 | 5,083 |
| Terminal-Bench | 17.1% | — |
| APEX-Agents | — | 37.6% |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| GBAEval | — | 0.9% |
Reasoning Kimi K2.7 Code leads
Gemini 2.5 Flash: 18.1 (#286), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| SimpleBench | 41.2% | 57.9% |
| CritPt | 1.1% | 10% |
| Epoch Capabilities Index | 143.03 | 149.97 |
| ARC-AGI-2 | 2.5% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| Chess Puzzles | — | 21% |
| EnigmaEval | 2.7% | — |
| LMArena Hard Prompts | 1422 | — |
| DTBench | 76.5% | — |
| LMCA | 27.5% | — |
| Surface Evolver Bench | — | 48.8% |
| ForecastBench | 60.6 | — |
Math Kimi K2.7 Code leads
Gemini 2.5 Flash: 39.9 (#98), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | 95.6% |
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| Omni-MATH | 38.5% | — |
| LMArena Math | 1415 | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Kimi K2.7 Code leads
Gemini 2.5 Flash: 36.4 (#168), Kimi K2.7 Code: 53.5 (#57)
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | — | 87.9% |
| Humanity's Last Exam | 12.1% | — |
| SimpleQA Verified | — | 36.5% |
| 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), Kimi K2.7 Code: —
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| LMArena Vision | 1253 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |
Multilingual Not comparable
Gemini 2.5 Flash: 52.3 (#88), Kimi K2.7 Code: —
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| 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), Kimi K2.7 Code: —
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| IFEval | 89.8% | — |
| LMArena Instruction Following | 1405 | — |
Long Context Not comparable
Gemini 2.5 Flash: 47.5 (#17), Kimi K2.7 Code: —
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| Fiction.LiveBench | 77.8% | — |
| LMArena Longer Query | 1419 | — |
Writing & Preference Not comparable
Gemini 2.5 Flash: 53.8 (#157), Kimi K2.7 Code: —
| Benchmark | Gemini 2.5 Flash | Kimi K2.7 Code |
|---|---|---|
| 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 Kimi K2.7 Code?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 39.3 on the Noometry Index. Gemini 2.5 Flash costs 2.0× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash or Kimi K2.7 Code?
Gemini 2.5 Flash is cheaper. It lists at $0.30 per million input tokens and $2.50 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is Gemini 2.5 Flash or Kimi K2.7 Code better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 35.8 in the Noometry coding category.
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 Kimi K2.7 Code share?
7 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Kimi K2.7 Code has 19.