Claude Haiku 4.5 vs GPT-5.3-Codex
Claude Haiku 4.5 (2025) and GPT-5.3-Codex (2026) are agentic coding models from Anthropic and OpenAI. Claude Haiku 4.5 ships a 200k-token context window, while GPT-5.3-Codex ships a 400K-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 11.7 pts. On pricing, Claude Haiku 4.5 costs $0.8/1M input tokens versus $1.75/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Claude Haiku 4.5 is ~119% cheaper at $0.8/1M; pay for GPT-5.3-Codex only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Claude Haiku 4.5 | GPT-5.3-Codex |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 400K |
| Cheapest output | $4/1M tokens | $14/1M tokens |
| Provider routes | 7 tracked | 2 tracked |
| Shared benchmarks | 1 rows | SWE-bench Verified leader |
Decision tradeoffs
- Claude Haiku 4.5 has the lower cheapest tracked output price at $4/1M tokens.
- Claude Haiku 4.5 has broader tracked provider coverage for fallback and procurement flexibility.
- Claude Haiku 4.5 uniquely exposes Multimodal in local model data.
- Local decision data tags Claude Haiku 4.5 for Coding, RAG, and Agents.
- GPT-5.3-Codex leads the largest shared benchmark signal on SWE-bench Verified by 11.7 points.
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex uniquely exposes Reasoning 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 prices on this page.
Claude Haiku 4.5
$1,640
Cheapest tracked route: AWS Bedrock
GPT-5.3-Codex
$4,900
Cheapest tracked route: OpenRouter
Estimated monthly gap: $3,260. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.3-Codex is $10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Multimodal before moving production traffic.
- GPT-5.3-Codex adds Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Claude Haiku 4.5 is $10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
- Claude Haiku 4.5 adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2026-02-05 |
| Context window | 200k | 400K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-02 | 2025-08 |
Pricing and availability
| Pricing attribute | Claude Haiku 4.5 | GPT-5.3-Codex |
|---|---|---|
| Input price | $0.8/1M tokens | $1.75/1M tokens |
| Output price | $4/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | Claude Haiku 4.5 | GPT-5.3-Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
Benchmarks
| Benchmark | Claude Haiku 4.5 | GPT-5.3-Codex |
|---|---|---|
| SWE-bench Verified | 73.3 | 85.0 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has Claude Haiku 4.5 at 73.3 and GPT-5.3-Codex at 85, with GPT-5.3-Codex ahead by 11.7 points. The largest visible gap is 11.7 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: Claude Haiku 4.5 and reasoning mode: GPT-5.3-Codex. Both models share vision, function calling, tool use, and 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, Claude Haiku 4.5 lists $0.8/1M input and $4/1M output tokens, 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 Claude Haiku 4.5 lower by about $3.67 per million blended tokens. Availability is 7 providers versus 2, so concentration risk also matters.
Choose Claude Haiku 4.5 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 and larger context windows 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, Claude Haiku 4.5 or GPT-5.3-Codex?
GPT-5.3-Codex supports 400K tokens, while Claude Haiku 4.5 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Claude Haiku 4.5 or GPT-5.3-Codex?
Claude Haiku 4.5 is cheaper on tracked token pricing. Claude Haiku 4.5 costs $0.8/1M input and $4/1M 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 Claude Haiku 4.5 or GPT-5.3-Codex open source?
Claude Haiku 4.5 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, Claude Haiku 4.5 or GPT-5.3-Codex?
Both Claude Haiku 4.5 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, Claude Haiku 4.5 or GPT-5.3-Codex?
Claude Haiku 4.5 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 Claude Haiku 4.5 and GPT-5.3-Codex?
Claude Haiku 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, AWS Bedrock, and GCP Vertex AI. GPT-5.3-Codex is available on OpenRouter and OpenAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.