Model comparison
Gemini 2.5 Flash vs Llama 4 Scout
Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 27.7 on the Noometry Index. Llama 4 Scout costs 5.7× less per token, which makes it the better buy when Gemini 2.5 Flash's lead doesn't matter for your workload.
Last verified . 39 shared benchmarks.
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MetaSummary
- They share 39 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 10 categories and Llama 4 Scout in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemini 2.5 Flash leads 39.9 to 19.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 73.1% for Gemini 2.5 Flash and 7.8% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 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 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash | Llama 4 Scout | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 39.3 | 27.7 |
| Released | 2025-04-17 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 66K | 4K |
| Input $ / M tokens | $0.30 | $0.10 |
| Output $ / M tokens | $2.50 | $0.30 |
| Results tracked | 54 | 43 |
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Category by category
Coding Gemini 2.5 Flash leads
Gemini 2.5 Flash: 35.8 (#220), Llama 4 Scout: 20.2 (#339)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| SWE-bench Verified (bash only) | 28.7% | 9.1% |
| LMArena Coding | 1424 | 1286 |
| Aider Polyglot | 55.1% | — |
| SciCode | — | 17% |
| WeirdML | 41.9% | — |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 661.88 | — |
Agentic & Tool Use Gemini 2.5 Flash leads
Gemini 2.5 Flash: 30.8 (#74), Llama 4 Scout: 24.6 (#119)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | 56.2% | 28.1% |
| Terminal-Bench | 17.1% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |
Reasoning Gemini 2.5 Flash leads
Gemini 2.5 Flash: 18.1 (#286), Llama 4 Scout: 9.1 (#345)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| ARC-AGI-2 | 2.5% | 0% |
| Kagi LLM Benchmark | 56.8% | 36.9% |
| ARC-AGI-1 | 33.3% | 0.5% |
| CritPt | 1.1% | 0% |
| LMArena Hard Prompts | 1422 | 1266 |
| DTBench | 76.5% | 57.9% |
| LMCA | 27.5% | 12% |
| Epoch Capabilities Index | 143.03 | 129.64 |
| ForecastBench | 60.6 | 57.5 |
| SimpleBench | 41.2% | — |
| EnigmaEval | 2.7% | — |
Math Gemini 2.5 Flash leads
Gemini 2.5 Flash: 39.9 (#98), Llama 4 Scout: 19.6 (#286)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 73.1% | 7.8% |
| Omni-MATH | 38.5% | 37.3% |
| LMArena Math | 1415 | 1287 |
| FrontierMath (Feb 2025 set) | 4.8% | 0% |
| MATH Level 5 | — | 62.3% |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Gemini 2.5 Flash leads
Gemini 2.5 Flash: 36.4 (#168), Llama 4 Scout: 31.9 (#217)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| MMLU-Pro | 63.9% | 74.2% |
| Vectara Hallucination Rate | 7.8% | 7.7% |
| GPQA (HELM) | 39% | 50.7% |
| LMArena Expert | 1426 | 1235 |
| GPQA Diamond | — | 51.8% |
| Humanity's Last Exam | 12.1% | — |
| Confabulations | 16.8% | — |
Multimodal Gemini 2.5 Flash leads
Gemini 2.5 Flash: 41.8 (#32), Llama 4 Scout: 32.2 (#102)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1253 | 1118 |
| SpatialViz-Bench | 36.9% | 34.2% |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
Multilingual Gemini 2.5 Flash leads
Gemini 2.5 Flash: 52.3 (#88), Llama 4 Scout: 41.0 (#212)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1409 | 1252 |
| LMArena Chinese | 1450 | 1255 |
| LMArena French | 1433 | 1282 |
| LMArena German | 1418 | 1272 |
| LMArena Japanese | 1405 | 1206 |
| LMArena Korean | 1385 | 1207 |
| LMArena Russian | 1415 | 1263 |
| LMArena Spanish | 1421 | 1278 |
Instruction Following Gemini 2.5 Flash leads
Gemini 2.5 Flash: 75.7 (#54), Llama 4 Scout: 65.8 (#217)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| IFEval | 89.8% | 81.8% |
| LMArena Instruction Following | 1405 | 1248 |
Long Context Gemini 2.5 Flash leads
Gemini 2.5 Flash: 47.5 (#17), Llama 4 Scout: 27.5 (#294)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | 77.8% | 36% |
| LMArena Longer Query | 1419 | 1265 |
Writing & Preference Gemini 2.5 Flash leads
Gemini 2.5 Flash: 53.8 (#157), Llama 4 Scout: 37.0 (#261)
| Benchmark | Gemini 2.5 Flash | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1417 | 1279 |
| LMArena Creative Writing | 1400 | 1249 |
| EQ-Bench Creative Writing | 1137 | 783 |
| WildBench | 81.7% | 78% |
| LMArena Multi-Turn | 1408 | 1280 |
| Short-Story Creative Writing | 76.5% | — |
Frequently asked questions
Is Gemini 2.5 Flash better than Llama 4 Scout?
Gemini 2.5 Flash is the stronger model overall, scoring 39.3 to 27.7 on the Noometry Index. Llama 4 Scout costs 5.7× 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 Llama 4 Scout?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.
Is Gemini 2.5 Flash or Llama 4 Scout better for coding?
Gemini 2.5 Flash scores higher on coding benchmarks: 35.8 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash does, with 1.05M tokens against 128K.
How many benchmarks do Gemini 2.5 Flash and Llama 4 Scout share?
39 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Llama 4 Scout has 43.