GPT-5.5 vs Llama 3.1 405B Instruct
GPT-5.5 (2026) and Llama 3.1 405B Instruct (2024) are frontier reasoning models from OpenAI and AI at Meta. GPT-5.5 ships a 1.05m-token context window, while Llama 3.1 405B Instruct ships a 128k-token context window. On Massive Multitask Language Understanding, GPT-5.5 leads by 3.8 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.5 fits 8x more tokens; pick it for long-context work and Llama 3.1 405B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 1.05m | 128k |
| Cheapest output | $30/1M tokens | $2.40/1M tokens |
| Provider routes | 3 tracked | 11 tracked |
| Shared benchmarks | Massive Multitask Language Understanding leader | 1 rows |
Decision tradeoffs
- GPT-5.5 holds a shared-benchmark lead on Massive Multitask Language Understanding, ahead by 3.8 points.
- GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.5 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
- Llama 3.1 405B Instruct has the lower cheapest tracked output price at $2.40/1M tokens.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.5
$11,500
Cheapest tracked route/tier: OpenAI API 0-272K input tokens
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $8,980. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.5 and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.1 405B Instruct is $27.60/1M 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.
- No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and GPT-5.5; plan for SDK, billing, or endpoint changes.
- GPT-5.5 is $27.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.5 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-23 | 2024-07-23 |
| Context window | 1.05m | 128k |
| Parameters | — | 405B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Llama 3 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-12 | 2023-12 |
Pricing and availability
| Pricing attribute | GPT-5.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Input price |
| $2.40/1M tokens |
| Output price |
| $2.40/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5.5 | Llama 3.1 405B Instruct |
|---|---|---|
| Massive Multitask Language Understanding | 92.4 | 88.6 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has GPT-5.5 at 92.4 and Llama 3.1 405B Instruct at 88.6, with GPT-5.5 ahead by 3.8 points. The largest visible gap is 3.8 points on Massive Multitask Language Understanding, 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: GPT-5.5, multimodal input: GPT-5.5, reasoning mode: GPT-5.5, function calling: GPT-5.5, tool use: GPT-5.5, and code execution: GPT-5.5. 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-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output, while Llama 3.1 405B Instruct lists $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.1 405B Instruct lower by about $10.10 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 11, so concentration risk also matters.
Choose GPT-5.5 when coding workflow support and larger context windows are central to the workload. Choose Llama 3.1 405B 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.
FAQ
Which has a larger context window, GPT-5.5 or Llama 3.1 405B Instruct?
GPT-5.5 supports 1.05m tokens, while Llama 3.1 405B 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-5.5 or Llama 3.1 405B Instruct?
GPT-5.5 lists tiered pricing: 0-272K input tokens is $5/1M input and $30/1M output; 272K+ input tokens is $8/1M input and $36/1M output. Llama 3.1 405B Instruct lists $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.5 or Llama 3.1 405B Instruct open source?
GPT-5.5 is listed under Proprietary. Llama 3.1 405B 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 vision, GPT-5.5 or Llama 3.1 405B Instruct?
GPT-5.5 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, GPT-5.5 or Llama 3.1 405B Instruct?
GPT-5.5 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 GPT-5.5 and Llama 3.1 405B Instruct?
GPT-5.5 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.