GPT-5.4 vs Llama 3.1 70B Instruct
GPT-5.4 (2026) and Llama 3.1 70B Instruct (2024) are frontier reasoning models from OpenAI and AI at Meta. GPT-5.4 ships a not-yet-sourced context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On pricing, Llama 3.1 70B Instruct costs $0.4/1M input tokens versus $2.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.1 70B Instruct is ~525% cheaper at $0.4/1M; pay for GPT-5.4 only for coding workflow support.
Specs
| Released | 2026-03-05 | 2024-07-23 |
| Context window | — | 128K |
| Parameters | — | 70B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| GPT-5.4 | Llama 3.1 70B Instruct | |
|---|---|---|
| Input price | $2.5/1M tokens | $0.4/1M tokens |
| Output price | $15/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| GPT-5.4 | Llama 3.1 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: GPT-5.4, reasoning mode: GPT-5.4, function calling: GPT-5.4, tool use: GPT-5.4, and code execution: GPT-5.4. 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-5.4 lists $2.5/1M input and $15/1M 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 Llama 3.1 70B Instruct lower by about $5.85 per million blended tokens. Availability is 2 providers versus 11, so concentration risk also matters.
Choose GPT-5.4 when coding workflow support are central to the workload. Choose Llama 3.1 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. 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.
FAQ
Which is cheaper, GPT-5.4 or Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct is cheaper on tracked token pricing. GPT-5.4 costs $2.5/1M input and $15/1M 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-5.4 or Llama 3.1 70B Instruct open source?
GPT-5.4 is listed under Proprietary. 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 multimodal input, GPT-5.4 or Llama 3.1 70B Instruct?
GPT-5.4 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.
Which is better for reasoning mode, GPT-5.4 or Llama 3.1 70B Instruct?
GPT-5.4 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GPT-5.4 or Llama 3.1 70B Instruct?
GPT-5.4 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.
Where can I run GPT-5.4 and Llama 3.1 70B Instruct?
GPT-5.4 is available on OpenAI API and OpenRouter. Llama 3.1 70B Instruct is available on OctoAI API, Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. 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.