Claude Haiku 5.5 vs GPT-5.1-Codex-Mini
Updated October 21, 2026. 11 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Claude Haiku 5.5 for coding: it scores 75.9 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini.
GPT-5.1-Codex-Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 11
- Claude Haiku 5.5 only
- 51
- GPT-5.1-Codex-Mini only
- 11
- Like-for-like categories
- 5 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Claude Haiku 5.5
Claude Haiku 5.5 scores 75.9 against 6.2.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Haiku 5.5
Claude Haiku 5.5 leads, 43.4 against 20.4.
Same board, both measured
Web design
Design Arena: websites
Claude Haiku 5.5
Claude Haiku 5.5 leads, 1263 against 1111.
Same board, both measured
General
Vals Index
No call
Only Claude Haiku 5.5 has a Vals Index result, 58.7%.
Directional only
Long documents
Listed context window
Claude Haiku 5.5
Claude Haiku 5.5 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Claude Haiku 5.5
Claude Haiku 5.5 $0.0003, GPT-5.1-Codex-Mini $0.0013 per turn.
List prices
At a glance
- Coding index
- Claude Haiku 5.5 75.9 from 2 benchmarks, GPT-5.1-Codex-Mini 6.2 from 1 benchmark.
- Widest category
- Coding, 50.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: Claude Haiku 5.5 1569 against GPT-5.1-Codex-Mini 1253, 52.7 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 5.5 $0.50 against GPT-5.1-Codex-Mini $2.00 per million output tokens, 4.0x apart.
- Context window
- Claude Haiku 5.5 takes 1M tokens, GPT-5.1-Codex-Mini 400K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Claude Haiku 5.5 | Bars | GPT-5.1-Codex-Mini | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index20
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| LiveBench coding | 91.4% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev | 1586 | 1244 | Claude Haiku 5.5 |
| Terminal-Bench 4 (Vals AI) | 36.4% | Not measured | Only Claude Haiku 5.5 measured |
| Vibe Code Bench (Vals AI) | 90.4% | Not measured | Only Claude Haiku 5.5 measured |
| Code migration (Vals AI) | 44.6% | Not measured | Only Claude Haiku 5.5 measured |
| ProgramBench (Vals AI) | 2.5% | Not measured | Only Claude Haiku 5.5 measured |
| IOI (Vals AI) | 47.3% | Not measured | Only Claude Haiku 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 44.0% | Not measured | Only Claude Haiku 5.5 measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.4% | Not measured | Only Claude Haiku 5.5 measured |
| CyberBench (Vals AI) | 75.5% | Not measured | Only Claude Haiku 5.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 83.6% | Only GPT-5.1-Codex-Mini measured |
| SciCode | 55.0% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only GPT-5.1-Codex-Mini measured |
| Terminal-Bench | Not measured | 61.6% | Only GPT-5.1-Codex-Mini measured |
| FrontierCode | 46.4% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierSWE | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev: React | 1605 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev: HTML | 1569 | 1253 | Claude Haiku 5.5 |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 43.4 | 20.4 | Claude Haiku 5.5 |
| Epoch Capabilities Index | 159.3 | Not measured | Only Claude Haiku 5.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| LiveBench research | 81.9% | Not measured | Only Claude Haiku 5.5 measured |
| LiveBench browser | 80.0% | Not measured | Only Claude Haiku 5.5 measured |
| LiveBench long agentic | 57.6% | Not measured | Only Claude Haiku 5.5 measured |
| SREBench (Vals AI) | 5.7% | Not measured | Only Claude Haiku 5.5 measured |
| Finance Agent (Vals AI) | 54.1% | Not measured | Only Claude Haiku 5.5 measured |
| Tax Agent Bench (Vals AI) | 31.9% | Not measured | Only Claude Haiku 5.5 measured |
| Legal Research Bench (Vals AI) | 43.3% | Not measured | Only Claude Haiku 5.5 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only Claude Haiku 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 59.0% | Not measured | Only Claude Haiku 5.5 measured |
| BioMysteryBench (Vals AI) | 70.4% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only Claude Haiku 5.5 measured |
| Vals Science Index | 38.5% | Not measured | Only Claude Haiku 5.5 measured |
| τ²-Bench Telecom | Not measured | 62.9% | Only GPT-5.1-Codex-Mini measured |
| APEX-Agents | 56.1% | Not measured | Only Claude Haiku 5.5 measured |
| Vending-Bench 2 | $3,602 | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| LiveBench reasoning | 82.4% | Not measured | Only Claude Haiku 5.5 measured |
| MysteryMechanism (Vals AI) | 35.1% | Not measured | Only Claude Haiku 5.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 81.3% | Only GPT-5.1-Codex-Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 44.4% | 18.5% | Claude Haiku 5.5 |
| GPQA Diamond (Epoch AI run) | 89.6% | Not measured | Only Claude Haiku 5.5 measured |
| ARC-AGI | 89.0% | Not measured | Only Claude Haiku 5.5 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only Claude Haiku 5.5 measured |
| Chess puzzles | 55.0% | Not measured | Only Claude Haiku 5.5 measured |
| Mystery game puzzles | 30.0% | Not measured | Only Claude Haiku 5.5 measured |
| EBR-bench | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 91.7 | Only GPT-5.1-Codex-Mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 91.7% | Only GPT-5.1-Codex-Mini measured |
| OTIS Mock AIME | 98.9% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierMath, tiers 1 to 3 | 75.1% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierMath, tier 4 | 46.3% | Not measured | Only Claude Haiku 5.5 measured |
| ProofBench | 89.0% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 51.5% | Not measured | Only Claude Haiku 5.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 82.0% | Only GPT-5.1-Codex-Mini measured |
| SimpleQA Verified | 23.8% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1263 | 1111 | Claude Haiku 5.5 |
| Design Arena: UI components | 1295 | 1081 | Claude Haiku 5.5 |
| Design Arena: game dev | 1315 | 1093 | Claude Haiku 5.5 |
| Design Arena: data viz | 1292 | 1097 | Claude Haiku 5.5 |
| Design Arena: 3D | 1343 | 988 | Claude Haiku 5.5 |
| Design Arena: all code categories | 1279 | 1094 | Claude Haiku 5.5 |
| Design Arena: SVG | Not measured | 977 | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | Not measured | 1104 | Only GPT-5.1-Codex-Mini measured |
| LiveBench design | 83.1% | Not measured | Only Claude Haiku 5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| Vals Index | 58.7% | Not measured | Only Claude Haiku 5.5 measured |
| LiveBench data analysis | 53.1% | Not measured | Only Claude Haiku 5.5 measured |
| Public Benefits Bench (Vals AI) | 63.2% | Not measured | Only Claude Haiku 5.5 measured |
| SAGE (Vals AI) | 45.8% | Not measured | Only Claude Haiku 5.5 measured |
| MedScribe (Vals AI) | 89.5% | Not measured | Only Claude Haiku 5.5 measured |
| IFBench | Not measured | 67.9% | Only GPT-5.1-Codex-Mini measured |
| Long context reasoning (AA-LCR) | 82.7% | 66.7% | Claude Haiku 5.5 |
| DTBench | 95.0% | Not measured | Only Claude Haiku 5.5 measured |
| LMCA | 51.1% | Not measured | Only Claude Haiku 5.5 measured |
| Furniture assembly | 47.5% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 36 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 5.5 | GPT-5.1-Codex-Mini | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Claude Haiku 5.5 costs less
Repository review
50K input + 3K output tokens
Claude Haiku 5.5 costs less
Agent loop
200K input + 10K output tokens
Claude Haiku 5.5 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Anthropic Claude Haiku 5.5 | OpenAI GPT-5.1-Codex-Mini |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | October 7, 2026 | November 13, 2025 |
| Context window | 1M | 400K |
| Input $/Mtok | $0.10 | $0.25 |
| Output $/Mtok | $0.50 | $2.00 |
| Coding index | 75.9 | 6.2 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Haiku 5.5 better than GPT-5.1-Codex-Mini for coding?
Pick Claude Haiku 5.5 for coding: it scores 75.9 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini. GPT-5.1-Codex-Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Claude Haiku 5.5 or GPT-5.1-Codex-Mini?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; GPT-5.1-Codex-Mini costs $0.25 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Haiku 5.5 or GPT-5.1-Codex-Mini?
Claude Haiku 5.5, with 1M tokens against 400K.
How many benchmarks is the Claude Haiku 5.5 vs GPT-5.1-Codex-Mini comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. Claude Haiku 5.5's coding index rests on 2 independent benchmarks and GPT-5.1-Codex-Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.