Claude Haiku 5.5 vs GLM 4.5
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Claude Haiku 5.5 scores 75.9 and GLM 4.5 64.2 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking.
Pick Claude Haiku 5.5 when output tokens cost 4.4x less, or when the context window is larger, 1M against 131K tokens.
- Shared results
- 9
- Claude Haiku 5.5 only
- 53
- GLM 4.5 only
- 51
- Like-for-like categories
- 4 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
No call
75.9 against 64.2, from different benchmarks with none in common.
Directional only
Intelligence
AA Intelligence Index
Claude Haiku 5.5
Claude Haiku 5.5 leads, 43.4 against 12.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GLM 4.5 has a GPQA Diamond result, 72.2%.
Directional only
Math
AIME
No call
Only GLM 4.5 has a AIME result, 86.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 4.5 has a MMLU Pro result, 81.2%.
Directional only
Web design
Design Arena: websites
Claude Haiku 5.5
Claude Haiku 5.5 leads, 1263 against 1170.
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Claude Haiku 5.5
Claude Haiku 5.5 $0.0003, GLM 4.5 $0.0017 per turn.
List prices
At a glance
- Coding index
- Claude Haiku 5.5 75.9 from 2 benchmarks, GLM 4.5 64.2 from 1 benchmark.
- Widest category
- Reasoning, 31.4 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Claude Haiku 5.5 44.4% against GLM 4.5 13.0%, 31.4 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 5.5 $0.50 against GLM 4.5 $2.20 per million output tokens, 4.4x apart.
- Context window
- Claude Haiku 5.5 takes 1M tokens, GLM 4.5 131K.
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 | GLM 4.5 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 9 | 0 |
CodingDirectional onlyFour of these boards feed the Vibe Coding Index23 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 64.2% | Only GLM 4.5 measured |
| LiveBench coding | 91.4% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev | 1586 | Not measured | Only Claude Haiku 5.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 67.5% | Only GLM 4.5 measured |
| 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 | 73.8% | Only GLM 4.5 measured |
| SciCode | 55.0% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 22.0% | Only GLM 4.5 measured |
| FrontierCode | 46.4% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierSWE | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| WeirdML | Not measured | 40.6% | Only GLM 4.5 measured |
| ALE-Bench | Not measured | 344.8 | Only GLM 4.5 measured |
| LMArena Text: coding | Not measured | 1434 | Only GLM 4.5 measured |
| LMArena Text: software and IT | Not measured | 1440 | Only GLM 4.5 measured |
| LMArena WebDev: React | 1605 | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev: HTML | 1569 | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 43.4 | 12.8 | 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 | GLM 4.5 | 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 | 43.0% | Only GLM 4.5 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 | GLM 4.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 72.2% | Only GLM 4.5 measured |
| 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 | 78.2% | Only GLM 4.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 44.4% | 13.0% | 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 |
| LMArena Text: hard prompts | Not measured | 1429 | Only GLM 4.5 measured |
| LMArena Text: expert | Not measured | 1433 | Only GLM 4.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1429 | Only GLM 4.5 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 86.7% | Only GLM 4.5 measured |
| MATH 500 (Vals AI) | Not measured | 94.0% | Only GLM 4.5 measured |
| MGSM (Vals AI) | Not measured | 90.8% | Only GLM 4.5 measured |
| AA Math Index | Not measured | 73.7 | Only GLM 4.5 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.7% | Only GLM 4.5 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 |
| LMArena Text: math | Not measured | 1427 | Only GLM 4.5 measured |
| LMArena Text: mathematical work | Not measured | 1430 | Only GLM 4.5 measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 81.2% | Only GLM 4.5 measured |
| LegalBench (Vals AI) | Not measured | 75.6% | Only GLM 4.5 measured |
| CorpFin (Vals AI) | Not measured | 61.0% | Only GLM 4.5 measured |
| TaxEval (Vals AI) | Not measured | 72.4% | Only GLM 4.5 measured |
| MedQA (Vals AI) | Not measured | 90.0% | Only GLM 4.5 measured |
| MedCode (Vals AI) | 51.5% | Not measured | Only Claude Haiku 5.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.5% | Only GLM 4.5 measured |
| SimpleQA Verified | 23.8% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: science | Not measured | 1444 | Only GLM 4.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only GLM 4.5 measured |
| LMArena Text: legal and government | Not measured | 1438 | Only GLM 4.5 measured |
| LMArena Text: business and finance | Not measured | 1420 | Only GLM 4.5 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1263 | 1170 | Claude Haiku 5.5 |
| Design Arena: UI components | 1295 | 1144 | Claude Haiku 5.5 |
| Design Arena: game dev | 1315 | 1145 | Claude Haiku 5.5 |
| Design Arena: data viz | 1292 | 1159 | Claude Haiku 5.5 |
| Design Arena: 3D | 1343 | 1170 | Claude Haiku 5.5 |
| Design Arena: all code categories | 1279 | 1165 | Claude Haiku 5.5 |
| Design Arena: SVG | Not measured | 1096 | Only GLM 4.5 measured |
| LiveBench design | 83.1% | Not measured | Only Claude Haiku 5.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | 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 | 44.1% | Only GLM 4.5 measured |
| Long context reasoning (AA-LCR) | 82.7% | 52.7% | 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 |
| Creative writing (Lech Mazur) | Not measured | 73.4% | Only GLM 4.5 measured |
| Furniture assembly | 47.5% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text | Not measured | 1430 | Only GLM 4.5 measured |
| LMArena Text: instruction following | Not measured | 1404 | Only GLM 4.5 measured |
| LMArena Text: creative writing | Not measured | 1395 | Only GLM 4.5 measured |
| LMArena Text: English | Not measured | 1437 | Only GLM 4.5 measured |
| LMArena Text: non-English | Not measured | 1417 | Only GLM 4.5 measured |
| LMArena Text: Chinese | Not measured | 1465 | Only GLM 4.5 measured |
| LMArena Text: German | Not measured | 1407 | Only GLM 4.5 measured |
| LMArena Text: Japanese | Not measured | 1415 | Only GLM 4.5 measured |
| LMArena Text: Korean | Not measured | 1380 | Only GLM 4.5 measured |
| LMArena Text: French | Not measured | 1418 | Only GLM 4.5 measured |
| LMArena Text: Spanish | Not measured | 1454 | Only GLM 4.5 measured |
| LMArena Text: Russian | Not measured | 1413 | Only GLM 4.5 measured |
| LMArena Text: Polish | Not measured | 1422 | Only GLM 4.5 measured |
| LMArena Text: multi-turn | Not measured | 1415 | Only GLM 4.5 measured |
| LMArena Text: longer queries | Not measured | 1412 | Only GLM 4.5 measured |
| LMArena Text: writing and language | Not measured | 1403 | Only GLM 4.5 measured |
| LMArena Text: entertainment and media | Not measured | 1404 | Only GLM 4.5 measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.5 | 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 | Z.ai GLM 4.5 |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | October 7, 2026 | July 25, 2025 |
| Context window | 1M | 131K |
| Input $/Mtok | $0.10 | $0.60 |
| Output $/Mtok | $0.50 | $2.20 |
| Coding index | 75.9 | 64.2 |
| 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 GLM 4.5 for coding?
Claude Haiku 5.5 scores 75.9 and GLM 4.5 64.2 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking. Pick Claude Haiku 5.5 when output tokens cost 4.4x less, or when the context window is larger, 1M against 131K tokens.
Which is cheaper, Claude Haiku 5.5 or GLM 4.5?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; GLM 4.5 costs $0.60 and $2.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Haiku 5.5 or GLM 4.5?
Claude Haiku 5.5, with 1M tokens against 131K.
How many benchmarks is the Claude Haiku 5.5 vs GLM 4.5 comparison based on?
9 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 GLM 4.5's on 1. Where only one model has a result, the page says so instead of naming a winner.