GPT-4o (11-20) vs Llama 4 Maverick 17B Instruct FP8
GPT-4o (11-20) (2024) and Llama 4 Maverick 17B Instruct FP8 (2025) are compact production models from OpenAI and AI at Meta. GPT-4o (11-20) ships a 128k-token context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 4 Maverick 17B Instruct FP8 fits 8x more tokens; pick it for long-context work and GPT-4o (11-20) for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-4o (11-20) | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Best for | multimodal apps | multimodal apps, long-context analysis, and provider-routed production |
| Decision fit | Coding, Agents, and Long context | Coding, RAG, and Agents |
| Context window | 128k | 1m |
| Cheapest output | - | $0.60/1M tokens |
| Provider routes | 0 tracked | 10 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GPT-4o (11-20) uniquely exposes Code execution in local model data.
- Local decision data tags GPT-4o (11-20) for Coding, Agents, and Long context.
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Maverick 17B Instruct FP8 uniquely exposes Multimodal and Structured outputs in local model data.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 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.
GPT-4o (11-20)
Unavailable
No complete token price in local provider data
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-4o (11-20) and Llama 4 Maverick 17B Instruct FP8; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Code execution before moving production traffic.
- Llama 4 Maverick 17B Instruct FP8 adds Multimodal and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 4 Maverick 17B Instruct FP8 and GPT-4o (11-20); plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal and Structured outputs before moving production traffic.
- GPT-4o (11-20) adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-11-20 | 2025-04-05 |
| Context window | 128k | 1m |
| Parameters | 1.76T (8x222B MoE)* | 400B (17B active) |
| Architecture | Mixture of Experts | Mixture of Experts |
| License | Proprietary | Llama 4 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2023-10 | 2024-08 |
Pricing and availability
| Pricing attribute | GPT-4o (11-20) | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Input price | - | $0.15/1M tokens |
| Output price | - | $0.60/1M tokens |
| Providers | - |
Capabilities
| Capability | GPT-4o (11-20) | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on multimodal input: Llama 4 Maverick 17B Instruct FP8, structured outputs: Llama 4 Maverick 17B Instruct FP8, and code execution: GPT-4o (11-20). Both models share vision, 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.
Pricing coverage is uneven: GPT-4o (11-20) has no token price sourced yet and Llama 4 Maverick 17B Instruct FP8 has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 10. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-4o (11-20) when coding workflow support are central to the workload. Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, 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 has a larger context window, GPT-4o (11-20) or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while GPT-4o (11-20) supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GPT-4o (11-20) or Llama 4 Maverick 17B Instruct FP8 open source?
GPT-4o (11-20) is listed under Proprietary. Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 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-4o (11-20) or Llama 4 Maverick 17B Instruct FP8?
Both GPT-4o (11-20) and Llama 4 Maverick 17B Instruct FP8 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, GPT-4o (11-20) or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 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 structured outputs, GPT-4o (11-20) or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-4o (11-20) and Llama 4 Maverick 17B Instruct FP8?
GPT-4o (11-20) is available on the tracked providers still being sourced. Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.