Llama 3 70B Instruct vs o3
Llama 3 70B Instruct (2024) and o3 (2025) are frontier reasoning models from AI at Meta and OpenAI. Llama 3 70B Instruct ships a 8k-token context window, while o3 ships a 200k-token context window. On HumanEval, o3 leads by 24.1 pts. On pricing, Llama 3 70B Instruct costs $0.40/1M input tokens versus $2/1M 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 70B Instruct is ~400% cheaper at $0.40/1M; pay for o3 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Llama 3 70B Instruct | o3 |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding, RAG, and Agents |
| Context window | 8k | 200k |
| Cheapest output | $0.40/1M tokens | $8/1M tokens |
| Provider routes | 18 tracked | 3 tracked |
| Shared benchmarks | 1 rows | HumanEval leader |
Decision tradeoffs
- Llama 3 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- 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.
- o3 holds a shared-benchmark lead on HumanEval, ahead by 24.1 points.
- o3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- o3 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags o3 for Coding, RAG, and Agents.
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
o3
$3,600
Cheapest tracked route/tier: OpenAI API
Estimated monthly gap: $3,180. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- o3 is $7.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- o3 adds Vision, Multimodal, and Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Llama 3 70B Instruct is $7.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2025-04-16 |
| Context window | 8k | 200k |
| Parameters | 70B | — |
| Architecture | decoder only | decoder only |
| License | Llama 3 Community | Proprietary |
| Openness | Open weights | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2023-12 | 2024-06 |
Pricing and availability
| Pricing attribute | Llama 3 70B Instruct | o3 |
|---|---|---|
| Input price | $0.40/1M tokens | $2/1M tokens |
| Output price | $0.40/1M tokens | $8/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 70B Instruct | o3 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3 70B Instruct | o3 |
|---|---|---|
| HumanEval | 72.6 | 96.7 |
Deep dive
On shared benchmark coverage, HumanEval has Llama 3 70B Instruct at 72.6 and o3 at 96.7, with o3 ahead by 24.1 points. The largest visible gap is 24.1 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 vision: o3, multimodal input: o3, reasoning mode: o3, function calling: o3, tool use: o3, and code execution: o3. 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, Llama 3 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider, while o3 lists $2/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 70B Instruct lower by about $3.40 per million blended tokens. Availability is 18 providers versus 3, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose o3 when coding workflow support 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 o3?
o3 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, Llama 3 70B Instruct or o3?
Llama 3 70B Instruct is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.40/1M input and $0.40/1M output tokens. o3 costs $2/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 70B Instruct or o3 open source?
Llama 3 70B Instruct is listed under Llama 3 Community. o3 is listed under Proprietary. 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, Llama 3 70B Instruct or o3?
o3 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Llama 3 70B Instruct or o3?
o3 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 Llama 3 70B Instruct and o3?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. o3 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.