Claude Haiku 5.5 vs GLM 4.7 Flash
Claude Haiku 5.5 leads GLM 4.7 Flash on the Artificial Analysis Intelligence Index, 43.4 to 14.9, and GLM 4.7 Flash costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
Claude Haiku 5.5 or GLM 4.7 Flash: which to pick
Only Claude Haiku 5.5 has a coding score, 70.7 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.
Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
- Shared results
- 11
- Claude Haiku 5.5 only
- 52
- GLM 4.7 Flash only
- 32
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Only Claude Haiku 5.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Claude Haiku 5.5
Claude Haiku 5.5 leads, 43.4 against 14.9.
Same board, both measured
Web design
Design Arena: websites
Claude Haiku 5.5
Claude Haiku 5.5 leads, 1263 against 1194.
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 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.7 Flash
Claude Haiku 5.5 $0.0003, GLM 4.7 Flash $0.0003 per turn.
List prices
At a glance
- Coding index
- Claude Haiku 5.5 70.7 from 5 benchmarks, GLM 4.7 Flash not benchmarked.
- Widest category
- General, 41.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Claude Haiku 5.5 82.7% against GLM 4.7 Flash 41.7%, 41.0 points apart on a 0 to 100 scale.
- Output price
- Claude Haiku 5.5 $0.50 against GLM 4.7 Flash $0.40 per million output tokens, 1.3x apart.
- Context window
- Claude Haiku 5.5 takes 1M tokens, GLM 4.7 Flash 200K.
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 4.7 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index19 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | Leader |
|---|---|---|---|
| LiveBench coding | 91.4% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena WebDev | 1586 | Not measured | Only Claude Haiku 5.5 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 |
| SciCode | 55.0% | Not measured | Only Claude Haiku 5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 22.0% | Only GLM 4.7 Flash measured |
| FrontierCode | 46.4% | Not measured | Only Claude Haiku 5.5 measured |
| FrontierSWE | 43.8% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: coding | Not measured | 1382 | Only GLM 4.7 Flash measured |
| LMArena Text: software and IT | Not measured | 1389 | Only GLM 4.7 Flash 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 |
| SciCode | 9.2% | Not measured | Only Claude Haiku 5.5 measured |
| 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 | GLM 4.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 43.4 | 14.9 | 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 4.7 Flash | 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 | 98.8% | Only GLM 4.7 Flash 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 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | 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 | 58.1% | Only GLM 4.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 44.4% | 7.6% | Claude Haiku 5.5 |
| GPQA Diamond (Epoch AI run) | 89.6% | 60.5% | Claude Haiku 5.5 |
| 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 | 1356 | Only GLM 4.7 Flash measured |
| LMArena Text: expert | Not measured | 1357 | Only GLM 4.7 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1369 | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | 58.3% | Claude Haiku 5.5 |
| 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 | 1355 | Only GLM 4.7 Flash measured |
| LMArena Text: mathematical work | Not measured | 1369 | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 51.5% | Not measured | Only Claude Haiku 5.5 measured |
| SimpleQA Verified | 23.8% | Not measured | Only Claude Haiku 5.5 measured |
| LMArena Text: science | Not measured | 1358 | Only GLM 4.7 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1343 | Only GLM 4.7 Flash measured |
| LMArena Text: legal and government | Not measured | 1357 | Only GLM 4.7 Flash measured |
| LMArena Text: business and finance | Not measured | 1343 | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1263 | 1194 | Claude Haiku 5.5 |
| Design Arena: UI components | 1291 | 1208 | Claude Haiku 5.5 |
| Design Arena: game dev | 1314 | 1135 | Claude Haiku 5.5 |
| Design Arena: data viz | 1295 | 1123 | Claude Haiku 5.5 |
| Design Arena: 3D | 1343 | 1121 | Claude Haiku 5.5 |
| Design Arena: all code categories | 1278 | 1178 | Claude Haiku 5.5 |
| Design Arena: SVG | Not measured | 1038 | Only GLM 4.7 Flash 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 4.7 Flash | 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 | 60.8% | Only GLM 4.7 Flash measured |
| Long context reasoning (AA-LCR) | 82.7% | 41.7% | 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 |
| LMArena Text | Not measured | 1351 | Only GLM 4.7 Flash measured |
| LMArena Text: instruction following | Not measured | 1327 | Only GLM 4.7 Flash measured |
| LMArena Text: creative writing | Not measured | 1296 | Only GLM 4.7 Flash measured |
| LMArena Text: English | Not measured | 1373 | Only GLM 4.7 Flash measured |
| LMArena Text: non-English | Not measured | 1330 | Only GLM 4.7 Flash measured |
| LMArena Text: Chinese | Not measured | 1403 | Only GLM 4.7 Flash measured |
| LMArena Text: German | Not measured | 1336 | Only GLM 4.7 Flash measured |
| LMArena Text: Korean | Not measured | 1283 | Only GLM 4.7 Flash measured |
| LMArena Text: French | Not measured | 1332 | Only GLM 4.7 Flash measured |
| LMArena Text: Spanish | Not measured | 1350 | Only GLM 4.7 Flash measured |
| LMArena Text: Russian | Not measured | 1333 | Only GLM 4.7 Flash measured |
| LMArena Text: Polish | Not measured | 1291 | Only GLM 4.7 Flash measured |
| LMArena Text: multi-turn | Not measured | 1342 | Only GLM 4.7 Flash measured |
| LMArena Text: longer queries | Not measured | 1345 | Only GLM 4.7 Flash measured |
| LMArena Text: writing and language | Not measured | 1320 | Only GLM 4.7 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1304 | Only GLM 4.7 Flash measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Haiku 5.5 | GLM 4.7 Flash | 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
GLM 4.7 Flash costs less
Repository review
50K input + 3K output tokens
GLM 4.7 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 4.7 Flash 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 4.7 Flash |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | October 7, 2026 | January 19, 2026 |
| Context window | 1M | 200K |
| Input $/Mtok | $0.10 | $0.0653 |
| Output $/Mtok | $0.50 | $0.40 |
| Coding index | 70.7 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Haiku 5.5 better than GLM 4.7 Flash for coding?
Only Claude Haiku 5.5 has a coding score, 70.7 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. Pick GLM 4.7 Flash for output tokens 1.3x cheaper ($0.40 vs $0.50 per million).
Which is cheaper, Claude Haiku 5.5 or GLM 4.7 Flash?
Claude Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Haiku 5.5 or GLM 4.7 Flash?
Claude Haiku 5.5, with 1M tokens against 200K.
How many benchmarks is the Claude Haiku 5.5 vs GLM 4.7 Flash 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 5 independent benchmarks and GLM 4.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.