GPT-5.2 Codex vs Llama 4 Scout 17B
GPT-5.2 Codex (2025) and Llama 4 Scout 17B (2025) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a not-yet-sourced context window, while Llama 4 Scout 17B ships a 10m-token context window. On pricing, Llama 4 Scout 17B costs $0.17/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GPT-5.2 Codex is coding-specialized model, while Llama 4 Scout 17B is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.2 Codex | Llama 4 Scout 17B |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps and long-context analysis |
| Decision fit | Coding, Agents, and Vision | RAG, Long context, and Vision |
| Context window | — | 10m |
| Cheapest output | $14/1M tokens | $0.66/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.2 Codex uniquely exposes Vision, Reasoning, and Function calling in local model data.
- Local decision data tags GPT-5.2 Codex for Coding, Agents, and Vision.
- Llama 4 Scout 17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Scout 17B has the lower cheapest tracked output price at $0.66/1M tokens.
- Llama 4 Scout 17B uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 4 Scout 17B for RAG, Long context, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.2 Codex
$4,900
Cheapest tracked route/tier: Vercel AI Gateway
Llama 4 Scout 17B
$301
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $4,599. 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-5.2 Codex and Llama 4 Scout 17B; plan for SDK, billing, or endpoint changes.
- Llama 4 Scout 17B is $13.34/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Reasoning, and Function calling before moving production traffic.
- Llama 4 Scout 17B adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 4 Scout 17B and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.2 Codex is $13.34/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- GPT-5.2 Codex adds Vision, Reasoning, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-18 | 2025-10-01 |
| Context window | — | 10m |
| Parameters | — | 17 |
| Architecture | decoder only | - |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-08 | 2024-08 |
Pricing and availability
| Pricing attribute | GPT-5.2 Codex | Llama 4 Scout 17B |
|---|---|---|
| Input price | $1.75/1M tokens | $0.17/1M tokens |
| Output price | $14/1M tokens | $0.66/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.2 Codex | Llama 4 Scout 17B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | 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 rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.2 Codex, reasoning mode: GPT-5.2 Codex, function calling: GPT-5.2 Codex, tool use: GPT-5.2 Codex, structured outputs: Llama 4 Scout 17B, and code execution: GPT-5.2 Codex. Both models share multimodal input, 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-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Llama 4 Scout 17B lists $0.17/1M input and $0.66/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Scout 17B lower by about $5.11 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose GPT-5.2 Codex when coding workflow support are central to the workload. Choose Llama 4 Scout 17B when provider fit 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 is cheaper, GPT-5.2 Codex or Llama 4 Scout 17B?
Llama 4 Scout 17B is cheaper on tracked token pricing. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Llama 4 Scout 17B costs $0.17/1M input and $0.66/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.2 Codex or Llama 4 Scout 17B open source?
GPT-5.2 Codex is listed under Proprietary. Llama 4 Scout 17B 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-5.2 Codex or Llama 4 Scout 17B?
GPT-5.2 Codex 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-5.2 Codex or Llama 4 Scout 17B?
Both GPT-5.2 Codex and Llama 4 Scout 17B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for reasoning mode, GPT-5.2 Codex or Llama 4 Scout 17B?
GPT-5.2 Codex 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.
Where can I run GPT-5.2 Codex and Llama 4 Scout 17B?
GPT-5.2 Codex is available on Vercel AI Gateway. Llama 4 Scout 17B is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.