Model comparison
Claude Haiku 4.5 vs GPT-5.3 Codex
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Haiku 4.5 #77 (Estimated); GPT-5.3 Codex #26 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Haiku 4.5 and GPT-5.3 Codex share 3 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Claude Haiku 4.5; 18 to GPT-5.3 Codex.
Updated July 20, 2026- Shared results
- 3
- Claude Haiku 4.5 only
- 2
- GPT-5.3 Codex only
- 18
- Comparable categories
- 1 / 8
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex is clearly ahead on the BenchAlign aggregate, 66.69 to 56.58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $1.00 input / $5.00 output per 1M tokens for Claude Haiku 4.5. That is roughly 2.8x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while Claude Haiku 4.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.3 Codex gives you the larger context window at 400K, compared with 200K for Claude Haiku 4.5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Claude Haiku 4.5 | Δ | GPT-5.3 Codex |
|---|---|---|---|
| Coding | Claude Haiku 4.573.3 | Margin← 6.1 | GPT-5.3 Codex67.2 |
| Agentic | Claude Haiku 4.5Not measured | MarginNo overlap | GPT-5.3 Codex71.4 |
| Math | Claude Haiku 4.54.9 | MarginNo overlap | GPT-5.3 CodexNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 73.3%B 85%Winner: GPT-5.3 CodexΔ 11.7SWE-bench Verified: Claude Haiku 4.5 scored 73.3%; GPT-5.3 Codex scored 85%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Haiku 4.5 | GPT-5.3 Codex | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Haiku 4.5$1 input / $5 output | GPT-5.3 Codex$1.75 input / $14 output | Claude Haiku 4.5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Haiku 4.5Not available | GPT-5.3 Codex79 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Haiku 4.5Not available | GPT-5.3 Codex88.26 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Haiku 4.5200K | GPT-5.3 Codex400K | GPT-5.3 Codex lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
CodingClaude Haiku 4.5 wins5 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Claude Haiku 4.5 | GPT-5.3 Codex | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 44.3% | Not comparable |
| AA-GPQA DiamondSource | — | 91.5% | Not comparable |
| AA-HLESource | — | 39.9% | Not comparable |
| AA-Omniscience IndexSource | — | 9.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 51.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 86.9% | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Haiku 4.5 | GPT-5.3 Codex | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.4% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude Haiku 4.5 or GPT-5.3 Codex?
GPT-5.3 Codex is ahead on BenchLM's BenchAlign leaderboard, 66.69 to 56.58. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 85%.
Which is better for coding, Claude Haiku 4.5 or GPT-5.3 Codex?
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 67.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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