GPT-5.3-Codex vs Llama 3.2 11B Instruct
GPT-5.3-Codex (2026) and Llama 3.2 11B Instruct (2025) are agentic coding models from OpenAI and AI at Meta. GPT-5.3-Codex ships a 400K-token context window, while Llama 3.2 11B Instruct ships a not-yet-sourced context window. On pricing, Llama 3.2 11B Instruct costs $0.2/1M input tokens versus $1.75/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.2 11B Instruct is ~775% cheaper at $0.2/1M; pay for GPT-5.3-Codex only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GPT-5.3-Codex | Llama 3.2 11B Instruct |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Classification and JSON / Tool use |
| Context window | 400K | — |
| Cheapest output | $14/1M tokens | $0.27/1M tokens |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.3-Codex uniquely exposes Vision, Reasoning, and Function calling in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Local decision data tags Llama 3.2 11B Instruct for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GPT-5.3-Codex
$4,900
Cheapest tracked route: OpenRouter
Llama 3.2 11B Instruct
$228
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $4,673. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.3-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 Vision, Reasoning, and Function calling before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.2 11B Instruct and GPT-5.3-Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.3-Codex is $13.73/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.3-Codex adds Vision, Reasoning, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-05 | 2025-09-01 |
| Context window | 400K | — |
| Parameters | — | — |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex | Llama 3.2 11B Instruct |
|---|---|---|
| Input price | $1.75/1M tokens | $0.2/1M tokens |
| Output price | $14/1M tokens | $0.27/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex | Llama 3.2 11B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.3-Codex, reasoning mode: GPT-5.3-Codex, function calling: GPT-5.3-Codex, tool use: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. 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-5.3-Codex lists $1.75/1M input and $14/1M output tokens, while Llama 3.2 11B Instruct lists $0.2/1M 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 $5.2 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose GPT-5.3-Codex when coding workflow support and broader provider choice are central to the workload. Choose Llama 3.2 11B Instruct 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. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, GPT-5.3-Codex or Llama 3.2 11B Instruct?
Llama 3.2 11B Instruct is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Llama 3.2 11B Instruct costs $0.2/1M input and $0.27/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.3-Codex or Llama 3.2 11B Instruct open source?
GPT-5.3-Codex is listed under Proprietary. Llama 3.2 11B Instruct is listed under Proprietary. 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-5.3-Codex or Llama 3.2 11B Instruct?
GPT-5.3-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 reasoning mode, GPT-5.3-Codex or Llama 3.2 11B Instruct?
GPT-5.3-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.
Which is better for function calling, GPT-5.3-Codex or Llama 3.2 11B Instruct?
GPT-5.3-Codex has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Llama 3.2 11B Instruct?
GPT-5.3-Codex is available on OpenRouter and OpenAI API. 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: 2026-05-11. Data sourced from public model cards and provider documentation.