Claude Haiku 4.5 vs Llama 3.2 11B Instruct
Claude Haiku 4.5 (2025) and Llama 3.2 11B Instruct (2025) are compact production models from Anthropic and AI at Meta. Claude Haiku 4.5 ships a 200k-token context window, while Llama 3.2 11B Instruct ships a 128k-token context window. On pricing, Llama 3.2 11B Instruct costs $0.20/1M input tokens versus $0.80/1M 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.
Llama 3.2 11B Instruct is ~300% cheaper at $0.20/1M; pay for Claude Haiku 4.5 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Claude Haiku 4.5 | Llama 3.2 11B Instruct |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | multimodal apps |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Vision |
| Context window | 200k | 128k |
| Cheapest output | $4/1M tokens | $0.27/1M tokens |
| Provider routes | 8 tracked | 1 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 has broader tracked provider coverage for fallback and procurement flexibility.
- Claude Haiku 4.5 uniquely exposes Function calling, Tool use, and Code execution in local model data.
- Local decision data tags Claude Haiku 4.5 for Coding, RAG, and Agents.
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Local decision data tags Llama 3.2 11B Instruct for RAG, Long context, and Vision.
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 3.2 11B Instruct
$228
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $1,413. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.2 11B Instruct is $3.73/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling, Tool use, and Code execution before moving production traffic.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Claude Haiku 4.5 is $3.73/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Haiku 4.5 adds Function calling, Tool use, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2025-09-01 |
| Context window | 200k | 128k |
| Parameters | — | 11B |
| Architecture | 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 3.2 11B Instruct |
|---|---|---|
| Input price | $0.80/1M tokens | $0.20/1M tokens |
| Output price | $4/1M tokens | $0.27/1M tokens |
| Providers |
Capabilities
| Capability | Claude Haiku 4.5 | Llama 3.2 11B Instruct |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| 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 function calling: Claude Haiku 4.5, tool use: Claude Haiku 4.5, and code execution: Claude Haiku 4.5. Both models share vision, multimodal input, and 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 3.2 11B Instruct lists $0.20/1M input and $0.27/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 11B Instruct lower by about $1.54 per million blended tokens. Availability is 8 providers versus 1, so concentration risk also matters.
Choose Claude Haiku 4.5 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Llama 3.2 11B Instruct when vision-heavy evaluation and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Claude Haiku 4.5 or Llama 3.2 11B Instruct?
Claude Haiku 4.5 supports 200k tokens, while Llama 3.2 11B 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 3.2 11B Instruct?
Llama 3.2 11B Instruct is cheaper on tracked token pricing. Claude Haiku 4.5 costs $0.80/1M input and $4/1M output tokens. Llama 3.2 11B Instruct costs $0.20/1M input and $0.27/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Haiku 4.5 or Llama 3.2 11B Instruct open source?
Claude Haiku 4.5 is listed under Proprietary. Llama 3.2 11B 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 3.2 11B Instruct?
Both Claude Haiku 4.5 and Llama 3.2 11B Instruct expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Claude Haiku 4.5 or Llama 3.2 11B Instruct?
Both Claude Haiku 4.5 and Llama 3.2 11B Instruct expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Claude Haiku 4.5 and Llama 3.2 11B Instruct?
Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. Llama 3.2 11B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.