GPT-5 vs Llama 4 Maverick 17B Instruct FP8
GPT-5 (2025) and Llama 4 Maverick 17B Instruct FP8 (2025) are frontier reasoning models from OpenAI and AI at Meta. GPT-5 ships a 400k-token context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window. On pricing, Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 4 Maverick 17B Instruct FP8 is ~733% cheaper at $0.15/1M; pay for GPT-5 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-5 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | long-context analysis and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 400k | 1m |
| Cheapest output | $10/1M tokens | $0.60/1M tokens |
| Provider routes | 4 tracked | 8 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags GPT-5 for Coding, RAG, and Agents.
- 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 the lower cheapest tracked output price at $0.60/1M tokens.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5
$3,500
Cheapest tracked route/tier: Replicate API
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $3,230. 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.
- Llama 4 Maverick 17B Instruct FP8 is $9.40/1M 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.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5 is $9.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-07 | 2025-04-05 |
| Context window | 400k | 1m |
| Parameters | — | 17B |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2024-09 | 2024-08 |
Pricing and availability
| Pricing attribute | GPT-5 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Input price | $1.25/1M tokens | $0.15/1M tokens |
| Output price | $10/1M tokens | $0.60/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| 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
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5, multimodal input: GPT-5, reasoning mode: GPT-5, function calling: GPT-5, tool use: GPT-5, and code execution: GPT-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 lists $1.25/1M input and $10/1M output tokens on the cheapest tracked provider, while Llama 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.60/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct FP8 lower by about $3.59 per million blended tokens. Availability is 4 providers versus 8, so concentration risk also matters.
Choose GPT-5 when coding workflow support are central to the workload. Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, and lower input-token cost 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.
FAQ
Which has a larger context window, GPT-5 or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while GPT-5 supports 400k 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 or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 is cheaper on tracked token pricing. GPT-5 costs $1.25/1M input and $10/1M output tokens. Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input and $0.60/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5 or Llama 4 Maverick 17B Instruct FP8 open source?
GPT-5 is listed under Proprietary. Llama 4 Maverick 17B Instruct FP8 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 vision, GPT-5 or Llama 4 Maverick 17B Instruct FP8?
GPT-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 or Llama 4 Maverick 17B Instruct FP8?
GPT-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 and Llama 4 Maverick 17B Instruct FP8?
GPT-5 is available on Replicate API, OpenRouter, OpenAI API, and Vercel AI Gateway. 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: 2026-05-22. Data sourced from public model cards and provider documentation.