Model comparison
Gemma 4 26B A4B IT vs Llama 4 Scout
Gemma 4 26B A4B IT is the stronger model overall, scoring 43.5 to 27.7 on the Noometry Index.
Last verified . 24 shared benchmarks.
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MetaSummary
- They share 24 benchmarks with published results for both. Gemma 4 26B A4B IT scores higher in 9 categories and Llama 4 Scout in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Gemma 4 26B A4B IT leads 47.6 to 19.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 82.2% for Gemma 4 26B A4B IT and 7.8% for Llama 4 Scout.
- Gemma 4 26B A4B IT is cheaper at $0.0675 / $0.23 per million input/output tokens, against $0.10 / $0.30 for Llama 4 Scout.
- Gemma 4 26B A4B IT accepts more context: 262K tokens versus 128K.
Side by side
| Gemma 4 26B A4B IT | Llama 4 Scout | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 43.5 | 27.7 |
| Released | 2026-04-02 | 2025-04-05 |
| Weights | Open | Open |
| Context window | 262K | 128K |
| Max output | 33K | 4K |
| Input $ / M tokens | $0.0675 | $0.10 |
| Output $ / M tokens | $0.23 | $0.30 |
| Results tracked | 28 | 43 |
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Category by category
Coding Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 39.0 (#164), Llama 4 Scout: 20.2 (#339)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| SciCode | 40% | 17% |
| LMArena Coding | 1447 | 1286 |
| SWE-bench Verified (bash only) | — | 9.1% |
| LMArena WebDev | 1359 | — |
| WeirdML | 35.2% | — |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 927.17 | — |
Agentic & Tool Use Not comparable
Gemma 4 26B A4B IT: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 21.8 (#213), Llama 4 Scout: 9.1 (#345)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1439 | 1266 |
| DTBench | 74.9% | 57.9% |
| LMCA | 29.7% | 12% |
| Epoch Capabilities Index | 141.85 | 129.64 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| Chess Puzzles | 6% | — |
| ForecastBench | — | 57.5 |
Math Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 47.6 (#67), Llama 4 Scout: 19.6 (#286)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 82.2% | 7.8% |
| LMArena Math | 1470 | 1287 |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 45.7 (#85), Llama 4 Scout: 31.9 (#217)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 73.2% | 51.8% |
| Vectara Hallucination Rate | 5.2% | 7.7% |
| LMArena Expert | 1447 | 1235 |
| MMLU-Pro | — | 74.2% |
| GPQA (HELM) | — | 50.7% |
Multimodal Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 40.6 (#46), Llama 4 Scout: 32.2 (#102)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| LMArena Vision | 1260 | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 53.1 (#71), Llama 4 Scout: 41.0 (#212)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1421 | 1252 |
| LMArena Chinese | 1495 | 1255 |
| LMArena French | 1460 | 1282 |
| LMArena Russian | 1434 | 1263 |
| LMArena Spanish | 1417 | 1278 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1206 |
| LMArena Korean | — | 1207 |
Instruction Following Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 74.8 (#82), Llama 4 Scout: 65.8 (#217)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1420 | 1248 |
| IFEval | — | 81.8% |
Long Context Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 43.6 (#91), Llama 4 Scout: 27.5 (#294)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1428 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Gemma 4 26B A4B IT leads
Gemma 4 26B A4B IT: 58.6 (#115), Llama 4 Scout: 37.0 (#261)
| Benchmark | Gemma 4 26B A4B IT | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1434 | 1279 |
| LMArena Creative Writing | 1402 | 1249 |
| EQ-Bench Creative Writing | 1305 | 783 |
| LMArena Multi-Turn | 1441 | 1280 |
| WildBench | — | 78% |
Frequently asked questions
Is Gemma 4 26B A4B IT better than Llama 4 Scout?
Gemma 4 26B A4B IT is the stronger model overall, scoring 43.5 to 27.7 on the Noometry Index.
Which is cheaper, Gemma 4 26B A4B IT or Llama 4 Scout?
Gemma 4 26B A4B IT is cheaper. It lists at $0.0675 per million input tokens and $0.23 per million output tokens; Llama 4 Scout lists at $0.10 and $0.30.
Is Gemma 4 26B A4B IT or Llama 4 Scout better for coding?
Gemma 4 26B A4B IT scores higher on coding benchmarks: 39.0 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Gemma 4 26B A4B IT does, with 262K tokens against 128K.
How many benchmarks do Gemma 4 26B A4B IT and Llama 4 Scout share?
24 benchmarks have published results for both models. Gemma 4 26B A4B IT has 28 scored results on Noometry and Llama 4 Scout has 43.