GPT-5.3-Codex vs Llama 3.1 70B Instruct
GPT-5.3-Codex (2026) and Llama 3.1 70B Instruct (2024) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex ships a 400k-token context window, while Llama 3.1 70B Instruct ships a 128k-token context window. On pricing, Llama 3.1 70B Instruct costs $0.40/1M 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-5.3-Codex is coding-specialized model, while Llama 3.1 70B 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-5.3-Codex | Llama 3.1 70B Instruct |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Long context |
| Context window | 400k | 128k |
| Cheapest output | $14/1M tokens | $0.40/1M tokens |
| Provider routes | 3 tracked | 13 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 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 3.1 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- Llama 3.1 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 70B Instruct for Coding, RAG, 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-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Llama 3.1 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Estimated monthly gap: $4,480. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Llama 3.1 70B Instruct is $13.60/1M 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.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.3-Codex is $13.60/1M 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 | 2024-07-23 |
| Context window | 400k | 128k |
| Parameters | — | 70B |
| Architecture | decoder only | 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-5.3-Codex | Llama 3.1 70B Instruct |
|---|---|---|
| Input price | $1.75/1M tokens | $0.40/1M tokens |
| Output price | $14/1M tokens | $0.40/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex | Llama 3.1 70B 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 |
| IDE integration | No | No |
| Computer use | Yes | 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-5.3-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 on the cheapest tracked provider, while Llama 3.1 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.1 70B Instruct lower by about $5.02 per million blended tokens. Availability is 3 providers versus 13, so concentration risk also matters.
Choose GPT-5.3-Codex when coding workflow support and larger context windows are central to the workload. Choose Llama 3.1 70B Instruct when provider fit, lower input-token cost, 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.
FAQ
Which has a larger context window, GPT-5.3-Codex or Llama 3.1 70B Instruct?
GPT-5.3-Codex supports 400k tokens, while Llama 3.1 70B Instruct supports 128k 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-5.3-Codex or Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Llama 3.1 70B Instruct costs $0.40/1M input and $0.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.3-Codex or Llama 3.1 70B Instruct open source?
GPT-5.3-Codex is listed under Proprietary. Llama 3.1 70B 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-5.3-Codex or Llama 3.1 70B 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 3.1 70B 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.
Where can I run GPT-5.3-Codex and Llama 3.1 70B Instruct?
GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Llama 3.1 70B Instruct is available on Cloudflare Workers AI, OctoAI API (Deprecated), Together AI, Fireworks AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-10. Data sourced from public model cards and provider documentation.