GPT-4 vs GPT-5.3-Codex
GPT-4 (2023) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. GPT-4 ships a 8k-token context window, while GPT-5.3-Codex ships a 400k-token context window. On pricing, GPT-5.3-Codex costs $1.75/1M input tokens versus $30/1M 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-4 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-4 | GPT-5.3-Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | multimodal apps, tool-calling agents, and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, Agents, and Vision | Coding, RAG, and Agents |
| Context window | 8k | 400k |
| Cheapest output | $60/1M tokens | $14/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-4 uniquely exposes Multimodal in local model data.
- Local decision data tags GPT-4 for Coding, Agents, and Vision.
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex has the lower cheapest tracked output price at $14/1M tokens.
- GPT-5.3-Codex uniquely exposes Reasoning and Tool use in local model data.
- 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-4
$39,000
Cheapest tracked route/tier: OpenAI API
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $34,100. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and OpenAI API; start route-level A/B tests there.
- GPT-5.3-Codex is $46/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Multimodal before moving production traffic.
- GPT-5.3-Codex adds Reasoning and Tool use in local capability data.
- Provider overlap exists on OpenAI API and OpenRouter; start route-level A/B tests there.
- GPT-4 is $46/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning and Tool use before moving production traffic.
- GPT-4 adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-03-14 | 2026-02-05 |
| Context window | 8k | 400k |
| Parameters | 1.76T (8x222B MoE)* | — |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Proprietary |
| Openness | Proprietary | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2021-09 | 2025-08 |
Pricing and availability
| Pricing attribute | GPT-4 | GPT-5.3-Codex |
|---|---|---|
| Input price | $30/1M tokens | $1.75/1M tokens |
| Output price | $60/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | GPT-4 | GPT-5.3-Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| 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 multimodal input: GPT-4, reasoning mode: GPT-5.3-Codex, and tool use: GPT-5.3-Codex. Both models share vision, function calling, structured outputs, and code execution, 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-4 lists $30/1M input and $60/1M 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-5.3-Codex lower by about $33.58 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.
Choose GPT-4 when coding workflow support and broader provider choice are central to the workload. Choose GPT-5.3-Codex when coding workflow support, larger context windows, 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 has a larger context window, GPT-4 or GPT-5.3-Codex?
GPT-5.3-Codex supports 400k tokens, while GPT-4 supports 8k 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-4 or GPT-5.3-Codex?
GPT-5.3-Codex is cheaper on tracked token pricing. GPT-4 costs $30/1M input and $60/1M 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-4 or GPT-5.3-Codex open source?
GPT-4 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-4 or GPT-5.3-Codex?
Both GPT-4 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-4 or GPT-5.3-Codex?
GPT-4 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-4 and GPT-5.3-Codex?
GPT-4 is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, and OpenRouter. 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.