Llama 3.1 405B vs Llama 3.1 70B Instruct
Llama 3.1 405B (2024) and Llama 3.1 70B Instruct (2024) are compact production models from AI at Meta. Llama 3.1 405B ships a 128k-token context window, while Llama 3.1 70B Instruct ships a 128k-token context window. On HumanEval, Llama 3.1 405B leads by 4.9 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3.1 405B is safer overall; choose Llama 3.1 70B Instruct when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B | Llama 3.1 70B Instruct |
|---|---|---|
| Best for | general production evaluation | provider-routed production |
| Decision fit | Coding, Long context, and Classification | Coding, RAG, and Long context |
| Context window | 128k | 128k |
| Cheapest output | - | $0.40/1M tokens |
| Provider routes | 0 tracked | 13 tracked |
| Shared benchmarks | HumanEval leader | 3 shared |
Decision tradeoffs
- Llama 3.1 405B holds a shared-benchmark lead on HumanEval, ahead by 4.9 points.
- Local decision data tags Llama 3.1 405B for Coding, Long context, and Classification.
- Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3.1 70B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.1 405B
Unavailable
No complete token price in local provider data
Llama 3.1 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3.1 405B and Llama 3.1 70B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.1 70B Instruct adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 3.1 70B Instruct and Llama 3.1 405B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2024-07-23 |
| Context window | 128k | 128k |
| Parameters | 405B | 70B |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 3 Community | Llama 3 Community |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2023-12 | 2023-12 |
Pricing and availability
| Pricing attribute | Llama 3.1 405B | Llama 3.1 70B Instruct |
|---|---|---|
| Input price | - | $0.40/1M tokens |
| Output price | - | $0.40/1M tokens |
| Providers | - |
Capabilities
| Capability | Llama 3.1 405B | Llama 3.1 70B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3.1 405B | Llama 3.1 70B Instruct |
|---|---|---|
| HumanEval | 89.0 | 84.1 |
| Massive Multitask Language Understanding | 88.6 | 86.0 |
| HellaSwag | 95.8 | 94.2 |
Deep dive
On shared benchmark coverage, HumanEval has Llama 3.1 405B at 89 and Llama 3.1 70B Instruct at 84.1, with Llama 3.1 405B ahead by 4.9 points; Massive Multitask Language Understanding has Llama 3.1 405B at 88.6 and Llama 3.1 70B Instruct at 86, with Llama 3.1 405B ahead by 2.6 points; HellaSwag has Llama 3.1 405B at 95.8 and Llama 3.1 70B Instruct at 94.2, with Llama 3.1 405B ahead by 1.6 points. The largest visible gap is 4.9 points on HumanEval, 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 structured outputs: Llama 3.1 70B Instruct. Both models share the core language-model surface, 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.
Pricing coverage is uneven: Llama 3.1 405B has no token price sourced yet and Llama 3.1 70B Instruct has $0.40/1M input tokens. Provider availability is 0 tracked routes versus 13. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 405B when provider fit are central to the workload. Choose Llama 3.1 70B 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, Llama 3.1 405B or Llama 3.1 70B Instruct?
Llama 3.1 405B supports 128k tokens, while Llama 3.1 70B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3.1 405B or Llama 3.1 70B Instruct open source?
Llama 3.1 405B is listed under Llama 3 Community. Llama 3.1 70B 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 structured outputs, Llama 3.1 405B or Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.1 405B and Llama 3.1 70B Instruct?
Llama 3.1 405B is available on the tracked providers still being sourced. Llama 3.1 70B Instruct is available on Cloudflare Workers AI, OctoAI API (Deprecated), Together AI, Fireworks AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.1 405B over Llama 3.1 70B Instruct?
Llama 3.1 405B is safer overall; choose Llama 3.1 70B Instruct when provider fit matters. If your workload also depends on provider fit, start with Llama 3.1 405B; if it depends on provider fit, run the same evaluation with Llama 3.1 70B Instruct.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.