Claude Haiku 4.5 vs Llama 4 Scout 17B Instruct
Llama 4 Scout 17B Instruct comes out ahead, 62 to 58 on our weighted score, and it is the cheaper option too.
AnthropicClaude Haiku 4.5
58/100- ECI142.4
- Price$1.00 / $5.00
- Context200K
- Our pick
MetaLlama 4 Scout 17B Instruct
62/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
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Make it a three-way comparison.
Llama 4 Scout 17B Instruct is our pick
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Claude Haiku 4.5 (58). It leads on price and context window. Claude Haiku 4.5 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Haiku 4.5Capabilities Index (ECI): Claude Haiku 4.5 142.4 · Llama 4 Scout 17B Instruct 129.7
- Lowest priceLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct $0.341 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · Claude Haiku 4.5 200,000 tokens
- Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · Llama 4 Scout 17B Instruct: Text, Images
- Self-hostingLlama 4 Scout 17B InstructPublishes downloadable weights
| Measure | Weight | Claude Haiku 4.5 | Llama 4 Scout 17B Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 69 | 52 |
| Price | 25% | 36 | 72 |
| Inputs & features | 15% | 80 | 50 |
| Context window | 10% | 32 | 100 |
| Overall | 100% | 58/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 4.5Anthropic | Llama 4 Scout 17B InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 142.4 (best) | 129.7 |
| ECI rank | #90 of 148 (best) | #126 of 148 |
| GPQA DiamondGraduate-level science questions | 71.2% (best) | 51.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.7% (best) | 7.8% |
| SimpleQA VerifiedShort factual questions | 13.2% | — |
| Price per million tokens | ||
| Input | $1.00 | $0.225 (best) |
| Output | $5.00 | $0.69 (best) |
| Cached input | $0.10 | — |
| Blended (3:1) | $2.00 | $0.341 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Anthropic API | Median of 4 providers |
| Limits | ||
| Context window | 200,000 tokens | 10,000,000 tokens (best) |
| Max output | 64,000 tokens (best) | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | claude-haiku-4-5 | — |
| API providers | 34 (best) | 4 |
| Released | Oct 15, 2025 | Apr 5, 2025 |
| Knowledge cutoff | Feb 28, 2025 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Haiku 4.5$20.00
- Llama 4 Scout 17B Instruct$3.63
Which should you choose?
Which is better: Claude Haiku 4.5 or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Claude Haiku 4.5 (58). It leads on price and context window. Claude Haiku 4.5 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 4.5 or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B Instruct is cheaper at $0.225 input / $0.69 output per million tokens (median across 4 API providers). Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.341 per million tokens for Llama 4 Scout 17B Instruct versus $2.00 for Claude Haiku 4.5 (5.9× as much).
Which scores higher on benchmarks?
Claude Haiku 4.5 scores higher on the Capabilities Index (ECI): Claude Haiku 4.5 142.4 (#90 of 148) and Llama 4 Scout 17B Instruct 129.7 (#126 of 148). Their confidence ranges do not overlap (139.5–144.3 vs 124.8–131.4), so the gap is a real one. On individual benchmarks: GPQA Diamond — Claude Haiku 4.5 71.2%, Llama 4 Scout 17B Instruct 51.8%; OTIS Mock AIME 2024–2025 — Claude Haiku 4.5 66.7%, Llama 4 Scout 17B Instruct 7.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 4.5 and Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 4.5 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 200,000 for Claude Haiku 4.5. Maximum output per response: Claude Haiku 4.5 up to 64,000, Llama 4 Scout 17B Instruct up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 4.5 accepts text, images and PDFs; Llama 4 Scout 17B Instruct accepts text and images. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Llama 4 Scout 17B Instruct publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.
Which is newer?
Claude Haiku 4.5 is the newest, released Oct 15, 2025. Llama 4 Scout 17B Instruct came out Apr 5, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, Llama 4 Scout 17B Instruct Aug 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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