GPT-5 vs GPT-5.3-Codex
GPT-5 (2025) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. GPT-5 ships a 400k-token context window, while GPT-5.3-Codex ships a 400k-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 10.1 pts. On pricing, GPT-5 costs $1.25/1M 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 is standalone API model, while GPT-5.3-Codex is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5 | GPT-5.3-Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 400k | 400k |
| Cheapest output | $10/1M tokens | $14/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | 1 rows | SWE-bench Verified leader |
Decision tradeoffs
- GPT-5 has the lower cheapest tracked output price at $10/1M tokens.
- GPT-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5 uniquely exposes Multimodal in local model data.
- Local decision data tags GPT-5 for Coding, RAG, and Agents.
- GPT-5.3-Codex leads the largest shared benchmark signal on SWE-bench Verified by 10.1 points.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
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
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,400. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, OpenAI API, and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.3-Codex is $4/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Multimodal before moving production traffic.
- Provider overlap exists on OpenRouter, OpenAI API, and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5 is $4/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- GPT-5 adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-07 | 2026-02-05 |
| Context window | 400k | 400k |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2024-09 | 2025-08 |
Pricing and availability
| Pricing attribute | GPT-5 | GPT-5.3-Codex |
|---|---|---|
| Input price | $1.25/1M tokens | $1.75/1M tokens |
| Output price | $10/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5 | GPT-5.3-Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5 | GPT-5.3-Codex |
|---|---|---|
| SWE-bench Verified | 74.9 | 85.0 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GPT-5 at 74.9 and GPT-5.3-Codex at 85, with GPT-5.3-Codex ahead by 10.1 points. The largest visible gap is 10.1 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on multimodal input: GPT-5. Both models share vision, reasoning mode, function calling, and tool use, 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 GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-5 lower by about $1.55 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.
Choose GPT-5 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.3-Codex when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5 or GPT-5.3-Codex?
GPT-5 supports 400k tokens, while GPT-5.3-Codex supports 400k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GPT-5 or GPT-5.3-Codex?
GPT-5 is cheaper on tracked token pricing. GPT-5 costs $1.25/1M input and $10/1M output tokens. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5 or GPT-5.3-Codex open source?
GPT-5 is listed under Proprietary. GPT-5.3-Codex 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 or GPT-5.3-Codex?
Both GPT-5 and GPT-5.3-Codex expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. 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 GPT-5.3-Codex?
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 GPT-5.3-Codex?
GPT-5 is available on Replicate API, OpenRouter, OpenAI API, and Vercel AI Gateway. GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.