Llama 3 70B Instruct vs Llama 3.1 70B Instruct
Llama 3 70B Instruct (2024) and Llama 3.1 70B Instruct (2024) are compact production models from AI at Meta. Llama 3 70B Instruct ships a 8k-token context window, while Llama 3.1 70B Instruct ships a 128k-token context window. On HumanEval, Llama 3.1 70B Instruct leads by 11.5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Pick Llama 3.1 70B Instruct for coding; token pricing is tied, so keep Llama 3 70B Instruct only for already-validated prompts or route constraints.
Decision scorecard
Local evidence first| Signal | Llama 3 70B Instruct | Llama 3.1 70B Instruct |
|---|---|---|
| Best for | provider-routed production | provider-routed production |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding, RAG, and Long context |
| Context window | 8k | 128k |
| Cheapest output | $0.40/1M tokens | $0.40/1M tokens |
| Provider routes | 18 tracked | 13 tracked |
| Shared benchmarks | 2 rows | HumanEval leader |
Decision tradeoffs
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
- Llama 3.1 70B Instruct holds a shared-benchmark lead on HumanEval, ahead by 11.5 points.
- Llama 3.1 70B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Llama 3.1 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Estimated monthly gap: $0.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OctoAI API (Deprecated), Together AI, and Fireworks AI; start route-level A/B tests there.
- Cheapest tracked output pricing is tied, so migration risk shifts to quality, latency, and provider packaging.
- Provider overlap exists on AWS Bedrock, Microsoft Foundry, and NVIDIA NIM; start route-level A/B tests there.
- Cheapest tracked output pricing is tied, so migration risk shifts to quality, latency, and provider packaging.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2024-07-23 |
| Context window | 8k | 128k |
| Parameters | 70B | 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 70B Instruct | Llama 3.1 70B Instruct |
|---|---|---|
| Input price | $0.40/1M tokens | $0.40/1M tokens |
| Output price | $0.40/1M tokens | $0.40/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 70B Instruct | Llama 3.1 70B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3 70B Instruct | Llama 3.1 70B Instruct |
|---|---|---|
| HumanEval | 72.6 | 84.1 |
| Massive Multitask Language Understanding | 82.0 | 86.0 |
Deep dive
On shared benchmark coverage, HumanEval has Llama 3 70B Instruct at 72.6 and Llama 3.1 70B Instruct at 84.1, with Llama 3.1 70B Instruct ahead by 11.5 points; Massive Multitask Language Understanding has Llama 3 70B Instruct at 82 and Llama 3.1 70B Instruct at 86, with Llama 3.1 70B Instruct ahead by 4 points. The largest visible gap is 11.5 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 is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Llama 3 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider, while Llama 3.1 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend is tied on the cheapest tracked routes. Availability is 18 providers versus 13, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit and broader provider choice are central to the workload. Choose Llama 3.1 70B Instruct when long-context analysis and larger context windows 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 70B Instruct or Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct supports 128k 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, Llama 3 70B Instruct or Llama 3.1 70B Instruct?
Neither is cheaper on tracked token pricing. Both list $0.40/1M input and $0.40/1M output tokens on the cheapest tracked route. Provider discounts, batch pricing, or route-specific tiers can still change the final bill.
Is Llama 3 70B Instruct or Llama 3.1 70B Instruct open source?
Llama 3 70B Instruct 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 70B Instruct or Llama 3.1 70B Instruct?
Both Llama 3 70B Instruct and Llama 3.1 70B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 3 70B Instruct and Llama 3.1 70B Instruct?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. 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 70B Instruct over Llama 3.1 70B Instruct?
Pick Llama 3.1 70B Instruct for coding; token pricing is tied, so keep Llama 3 70B Instruct only for already-validated prompts or route constraints. If your workload also depends on provider fit, start with Llama 3 70B Instruct; if it depends on long-context analysis, run the same evaluation with Llama 3.1 70B Instruct.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.