GPT-5.2 Codex vs Llama 3.2 11B Instruct
GPT-5.2 Codex (2025) and Llama 3.2 11B Instruct (2025) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a not-yet-sourced context window, while Llama 3.2 11B Instruct ships a 128k-token context window. On pricing, Llama 3.2 11B Instruct costs $0.20/1M 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 3.2 11B Instruct 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 3.2 11B Instruct |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps |
| Decision fit | Coding, Agents, and Vision | RAG, Long context, and Vision |
| Context window | — | 128k |
| Cheapest output | $14/1M tokens | $0.27/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.2 Codex uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GPT-5.2 Codex for Coding, Agents, and Vision.
- Llama 3.2 11B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Llama 3.2 11B Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 3.2 11B Instruct 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 3.2 11B Instruct
$228
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $4,673. 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 3.2 11B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.2 11B Instruct is $13.73/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Llama 3.2 11B Instruct adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 3.2 11B Instruct and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.2 Codex is $13.73/1M 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 Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-18 | 2025-09-01 |
| Context window | — | 128k |
| Parameters | — | 11B |
| Architecture | decoder only | - |
| License | Proprietary | Llama 3 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-08 | 2023-12 |
Pricing and availability
| Pricing attribute | GPT-5.2 Codex | Llama 3.2 11B Instruct |
|---|---|---|
| Input price | $1.75/1M tokens | $0.20/1M tokens |
| Output price | $14/1M tokens | $0.27/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.2 Codex | Llama 3.2 11B Instruct |
|---|---|---|
| Vision | Yes | Yes |
| 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 reasoning mode: GPT-5.2 Codex, function calling: GPT-5.2 Codex, tool use: GPT-5.2 Codex, structured outputs: Llama 3.2 11B Instruct, and code execution: GPT-5.2 Codex. Both models share vision and 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 3.2 11B Instruct lists $0.20/1M input and $0.27/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 11B Instruct lower by about $5.20 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 3.2 11B Instruct when vision-heavy evaluation 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 3.2 11B Instruct?
Llama 3.2 11B Instruct is cheaper on tracked token pricing. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Llama 3.2 11B Instruct costs $0.20/1M input and $0.27/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.2 Codex or Llama 3.2 11B Instruct open source?
GPT-5.2 Codex is listed under Proprietary. Llama 3.2 11B 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-5.2 Codex or Llama 3.2 11B Instruct?
Both GPT-5.2 Codex and Llama 3.2 11B Instruct 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-5.2 Codex or Llama 3.2 11B Instruct?
Both GPT-5.2 Codex and Llama 3.2 11B Instruct 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 3.2 11B Instruct?
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 3.2 11B Instruct?
GPT-5.2 Codex is available on Vercel AI Gateway. Llama 3.2 11B Instruct 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: 2026-06-04. Data sourced from public model cards and provider documentation.