Model comparison
Claude Haiku 4.5 vs Llama 4 Scout
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 27.7 on the Noometry Index. Llama 4 Scout costs 13× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Last verified . 37 shared benchmarks.
MetaSummary
- They share 37 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 9 categories and Llama 4 Scout in 1 category; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Haiku 4.5 leads 44.9 to 19.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 66.7% for Claude Haiku 4.5 and 7.8% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Claude Haiku 4.5 accepts more context: 200K tokens versus 128K.
- Llama 4 Scout has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Llama 4 Scout | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 39.5 | 27.7 |
| Released | 2025-10-15 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 200K | 128K |
| Max output | 64K | 4K |
| Input $ / M tokens | $1 | $0.10 |
| Output $ / M tokens | $5 | $0.30 |
| Results tracked | 53 | 43 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Llama 4 Scout: 20.2 (#339)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| SWE-bench Verified (bash only) | 66.6% | 9.1% |
| SciCode | 43.3% | 17% |
| LMArena Coding | 1453 | 1286 |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| WeirdML | 45.4% | — |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 653.48 | — |
Agentic & Tool Use Claude Haiku 4.5 leads
Claude Haiku 4.5: 33.6 (#52), Llama 4 Scout: 24.6 (#119)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | 68.7% | 28.1% |
| Terminal-Bench | 35.5% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Claude Haiku 4.5 leads
Claude Haiku 4.5: 15.1 (#320), Llama 4 Scout: 9.1 (#345)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| ARC-AGI-2 | 4% | 0% |
| ARC-AGI-1 | 47.7% | 0.5% |
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1420 | 1266 |
| DTBench | 73.6% | 57.9% |
| LMCA | 30.9% | 12% |
| Epoch Capabilities Index | 142.41 | 129.64 |
| ForecastBench | 61.4 | 57.5 |
| Kagi LLM Benchmark | — | 36.9% |
| NYT Connections (extended) | 14.3% | — |
| Chess Puzzles | 8% | — |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), Llama 4 Scout: 19.6 (#286)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 7.8% |
| Omni-MATH | 56.1% | 37.3% |
| LMArena Math | 1396 | 1287 |
| MATH Level 5 | 96.4% | 62.3% |
| FrontierMath (Feb 2025 set) | 5.9% | 0% |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.7 (#153), Llama 4 Scout: 31.9 (#217)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 71.2% | 51.8% |
| MMLU-Pro | 77.7% | 74.2% |
| Vectara Hallucination Rate | 9.8% | 7.7% |
| GPQA (HELM) | 60.5% | 50.7% |
| LMArena Expert | 1442 | 1235 |
| SimpleQA Verified | 13.2% | — |
Multimodal Llama 4 Scout leads
Claude Haiku 4.5: 26.8 (#118), Llama 4 Scout: 32.2 (#102)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
| SpatialViz-Bench | — | 34.2% |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 49.9 (#129), Llama 4 Scout: 41.0 (#212)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1377 | 1252 |
| LMArena Chinese | 1417 | 1255 |
| LMArena French | 1408 | 1282 |
| LMArena German | 1375 | 1272 |
| LMArena Japanese | 1339 | 1206 |
| LMArena Korean | 1347 | 1207 |
| LMArena Russian | 1381 | 1263 |
| LMArena Spanish | 1420 | 1278 |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.4 (#149), Llama 4 Scout: 65.8 (#217)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| IFEval | 80.1% | 81.8% |
| LMArena Instruction Following | 1414 | 1248 |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), Llama 4 Scout: 27.5 (#294)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1427 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 57.9 (#123), Llama 4 Scout: 37.0 (#261)
| Benchmark | Claude Haiku 4.5 | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1396 | 1279 |
| LMArena Creative Writing | 1372 | 1249 |
| WildBench | 83.9% | 78% |
| LMArena Multi-Turn | 1409 | 1280 |
| EQ-Bench Creative Writing | — | 783 |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Llama 4 Scout?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 27.7 on the Noometry Index. Llama 4 Scout costs 13× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Which is cheaper, Claude Haiku 4.5 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; Claude Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or Llama 4 Scout better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Claude Haiku 4.5 does, with 200K tokens against 128K.
How many benchmarks do Claude Haiku 4.5 and Llama 4 Scout share?
37 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Llama 4 Scout has 43.