Claude Sonnet 4.5 vs Llama 3 70B Instruct
Claude Sonnet 4.5 (2025) and Llama 3 70B Instruct (2024) are frontier reasoning models from Anthropic and AI at Meta. Claude Sonnet 4.5 ships a 200K-token context window, while Llama 3 70B Instruct ships a 8K-token context window. On MMLU PRO, Claude Sonnet 4.5 leads by 28.6 pts. On pricing, Llama 3 70B Instruct costs $0.4/1M input tokens versus $3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 70B Instruct is ~650% cheaper at $0.4/1M; pay for Claude Sonnet 4.5 only for reasoning depth.
Specs
| Released | 2025-09-29 | 2024-04-18 |
| Context window | 200K | 8K |
| Parameters | — | 70B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-12 | - |
Pricing and availability
| Claude Sonnet 4.5 | Llama 3 70B Instruct | |
|---|---|---|
| Input price | $3/1M tokens | $0.4/1M tokens |
| Output price | $15/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Claude Sonnet 4.5 | Llama 3 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Claude Sonnet 4.5 | Llama 3 70B Instruct |
|---|---|---|
| MMLU PRO | 86.0 | 57.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has Claude Sonnet 4.5 at 86 and Llama 3 70B Instruct at 57.4, with Claude Sonnet 4.5 ahead by 28.6 points. The largest visible gap is 28.6 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Claude Sonnet 4.5, multimodal input: Claude Sonnet 4.5, reasoning mode: Claude Sonnet 4.5, function calling: Claude Sonnet 4.5, and tool use: Claude Sonnet 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 Sonnet 4.5 lists $3/1M input and $15/1M output tokens, while Llama 3 70B Instruct lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 70B Instruct lower by about $6.2 per million blended tokens. Availability is 8 providers versus 18, so concentration risk also matters.
Choose Claude Sonnet 4.5 when reasoning depth and larger context windows are central to the workload. Choose Llama 3 70B Instruct when provider fit, lower input-token cost, 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 Sonnet 4.5 or Llama 3 70B Instruct?
Claude Sonnet 4.5 supports 200K tokens, while Llama 3 70B Instruct supports 8K 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 Sonnet 4.5 or Llama 3 70B Instruct?
Llama 3 70B Instruct is cheaper on tracked token pricing. Claude Sonnet 4.5 costs $3/1M input and $15/1M output tokens. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Sonnet 4.5 or Llama 3 70B Instruct open source?
Claude Sonnet 4.5 is listed under Proprietary. Llama 3 70B Instruct is listed under Open Source. 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 Sonnet 4.5 or Llama 3 70B Instruct?
Claude Sonnet 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 Sonnet 4.5 or Llama 3 70B Instruct?
Claude Sonnet 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 Sonnet 4.5 and Llama 3 70B Instruct?
Claude Sonnet 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, GCP Vertex AI, and AWS Bedrock. Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.