gpt-oss-120b vs Llama 3.1 70B Instruct
gpt-oss-120b (2025) and Llama 3.1 70B Instruct (2024) are compact production models from OpenAI and AI at Meta. gpt-oss-120b ships a 131K-token context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On pricing, gpt-oss-120b costs $0.04/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
gpt-oss-120b is ~926% cheaper at $0.04/1M; pay for Llama 3.1 70B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | gpt-oss-120b | Llama 3.1 70B Instruct |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Coding, RAG, and Long context |
| Context window | 131K | 128K |
| Cheapest output | $0.18/1M tokens | $0.4/1M tokens |
| Provider routes | 7 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- gpt-oss-120b has the larger context window for long prompts, retrieval packs, or transcript analysis.
- gpt-oss-120b has the lower cheapest tracked output price at $0.18/1M tokens.
- gpt-oss-120b uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags gpt-oss-120b for RAG, Agents, and Long context.
- Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- 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 prices on this page.
gpt-oss-120b
$76.20
Cheapest tracked route: OpenRouter
Llama 3.1 70B Instruct
$420
Cheapest tracked route: Hyperbolic AI Inference
Estimated monthly gap: $344. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Together AI, Fireworks AI, and NVIDIA NIM; start route-level A/B tests there.
- Llama 3.1 70B Instruct is $0.22/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Provider overlap exists on OpenRouter, Together AI, and Fireworks AI; start route-level A/B tests there.
- gpt-oss-120b is $0.22/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- gpt-oss-120b adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-05 | 2024-07-23 |
| Context window | 131K | 128K |
| Parameters | 120B | 70B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | gpt-oss-120b | Llama 3.1 70B Instruct |
|---|---|---|
| Input price | $0.04/1M tokens | $0.4/1M tokens |
| Output price | $0.18/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Capability | gpt-oss-120b | Llama 3.1 70B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: gpt-oss-120b and tool use: gpt-oss-120b. 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, gpt-oss-120b lists $0.04/1M input and $0.18/1M output tokens, while Llama 3.1 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 gpt-oss-120b lower by about $0.32 per million blended tokens. Availability is 7 providers versus 11, so concentration risk also matters.
Choose gpt-oss-120b when long-context analysis, larger context windows, and lower input-token cost 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, gpt-oss-120b or Llama 3.1 70B Instruct?
gpt-oss-120b supports 131K 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.
Which is cheaper, gpt-oss-120b or Llama 3.1 70B Instruct?
gpt-oss-120b is cheaper on tracked token pricing. gpt-oss-120b costs $0.04/1M input and $0.18/1M output tokens. Llama 3.1 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 gpt-oss-120b or Llama 3.1 70B Instruct open source?
gpt-oss-120b is listed under Open Source. Llama 3.1 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 function calling, gpt-oss-120b or Llama 3.1 70B Instruct?
gpt-oss-120b has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, gpt-oss-120b or Llama 3.1 70B Instruct?
gpt-oss-120b has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run gpt-oss-120b and Llama 3.1 70B Instruct?
gpt-oss-120b is available on OpenRouter, Together AI, Fireworks AI, GCP Vertex AI, and NVIDIA NIM. Llama 3.1 70B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.