Claude Haiku 4.5 vs Llama 3.1 405B Instruct
Claude Haiku 4.5 (2025) and Llama 3.1 405B Instruct (2024) are compact production models from Anthropic and AI at Meta. Claude Haiku 4.5 ships a 200k-token context window, while Llama 3.1 405B Instruct ships a 128k-token context window. On pricing, Claude Haiku 4.5 costs $0.80/1M input tokens versus $2.40/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Claude Haiku 4.5 is ~200% cheaper at $0.80/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Claude Haiku 4.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 200k | 128k |
| Cheapest output | $4/1M tokens | $2.40/1M tokens |
| Provider routes | 8 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Claude Haiku 4.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Claude Haiku 4.5 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Claude Haiku 4.5 for Coding, RAG, and Agents.
- Llama 3.1 405B Instruct has the lower cheapest tracked output price at $2.40/1M tokens.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Claude Haiku 4.5
$1,640
Cheapest tracked route/tier: AWS Bedrock
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $880. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Microsoft Foundry, AWS Bedrock, and GCP Vertex AI; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $1.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Provider overlap exists on Microsoft Foundry, AWS Bedrock, and GCP Vertex AI; start route-level A/B tests there.
- Claude Haiku 4.5 is $1.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Haiku 4.5 adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2024-07-23 |
| Context window | 200k | 128k |
| Parameters | — | 405B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Llama 3 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-02 | 2023-12 |
Pricing and availability
| Pricing attribute | Claude Haiku 4.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.80/1M tokens | $2.40/1M tokens |
| Output price | $4/1M tokens | $2.40/1M tokens |
| Providers |
Capabilities
| Capability | Claude Haiku 4.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Claude Haiku 4.5, multimodal input: Claude Haiku 4.5, function calling: Claude Haiku 4.5, tool use: Claude Haiku 4.5, and code execution: Claude Haiku 4.5. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Claude Haiku 4.5 lists $0.80/1M input and $4/1M output tokens on the cheapest tracked provider, while Llama 3.1 405B Instruct lists $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Claude Haiku 4.5 lower by about $0.64 per million blended tokens. Availability is 8 providers versus 11, so concentration risk also matters.
Choose Claude Haiku 4.5 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Claude Haiku 4.5 or Llama 3.1 405B Instruct?
Claude Haiku 4.5 supports 200k tokens, while Llama 3.1 405B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Claude Haiku 4.5 or Llama 3.1 405B Instruct?
Claude Haiku 4.5 is cheaper on tracked token pricing. Claude Haiku 4.5 costs $0.80/1M input and $4/1M output tokens. Llama 3.1 405B Instruct costs $2.40/1M input and $2.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Haiku 4.5 or Llama 3.1 405B Instruct open source?
Claude Haiku 4.5 is listed under Proprietary. Llama 3.1 405B Instruct is listed under Llama 3 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Claude Haiku 4.5 or Llama 3.1 405B Instruct?
Claude Haiku 4.5 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Claude Haiku 4.5 or Llama 3.1 405B Instruct?
Claude Haiku 4.5 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Claude Haiku 4.5 and Llama 3.1 405B Instruct?
Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-25. Data sourced from public model cards and provider documentation.