Model comparison
Claude Haiku 4.5 vs GLM-4.7-Flash
Claude Haiku 4.5 and GLM-4.7-Flash score almost the same on the Noometry Index (39.3 vs 38.4), so choose on price, context window or the category you care about most.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 7 categories and GLM-4.7-Flash in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Haiku 4.5 leads 58.1 to 47.7.
- The biggest single-benchmark swing is GPQA Diamond: 71.2% for Claude Haiku 4.5 and 60.5% for GLM-4.7-Flash.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | GLM-4.7-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 39.3 | 38.4 |
| Released | 2025-10-15 | 2026-01-19 |
| Weights | Proprietary | Open |
| Context window | 200K | 200K |
| Max output | 64K | 131K |
| Input $ / M tokens | $1 | $0.06 |
| Output $ / M tokens | $5 | $0.40 |
| Results tracked | 53 | 21 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.9 (#71), GLM-4.7-Flash: 40.0 (#133)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1454 | 1383 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| ALE-Bench | 653.48 | — |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.5 (#50), GLM-4.7-Flash: —
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning GLM-4.7-Flash leads
Claude Haiku 4.5: 15.1 (#310), GLM-4.7-Flash: 20.2 (#224)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| Chess Puzzles | 8% | 0% |
| LMArena Hard Prompts | 1420 | 1356 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| DTBench | 73.6% | — |
| LMCA | 30.9% | — |
| Epoch Capabilities Index | 142.42 | — |
| ForecastBench | 61.4 | — |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.0 (#69), GLM-4.7-Flash: 34.4 (#159)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 58.3% |
| LMArena Math | 1395 | 1354 |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.6 (#146), GLM-4.7-Flash: 35.4 (#177)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | 71.2% | 60.5% |
| Vectara Hallucination Rate | 9.8% | 9.3% |
| LMArena Expert | 1443 | 1357 |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 60.5% | — |
Multimodal Not comparable
Claude Haiku 4.5: 27.0 (#111), GLM-4.7-Flash: —
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 50.1 (#124), GLM-4.7-Flash: 46.8 (#152)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1376 | 1331 |
| LMArena Chinese | 1415 | 1403 |
| LMArena French | 1408 | 1332 |
| LMArena German | 1377 | 1336 |
| LMArena Korean | 1346 | 1284 |
| LMArena Russian | 1380 | 1333 |
| LMArena Spanish | 1420 | 1351 |
| LMArena Japanese | 1339 | — |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.6 (#144), GLM-4.7-Flash: 70.3 (#162)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1414 | 1327 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#86), GLM-4.7-Flash: 40.9 (#143)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1427 | 1345 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 58.1 (#119), GLM-4.7-Flash: 47.7 (#206)
| Benchmark | Claude Haiku 4.5 | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1396 | 1351 |
| LMArena Creative Writing | 1371 | 1297 |
| LMArena Multi-Turn | 1409 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than GLM-4.7-Flash?
Claude Haiku 4.5 and GLM-4.7-Flash score almost the same on the Noometry Index (39.3 vs 38.4), so choose on price, context window or the category you care about most.
Which is cheaper, Claude Haiku 4.5 or GLM-4.7-Flash?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Claude Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or GLM-4.7-Flash better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 43.9 versus 40.0 in the Noometry coding category.
Which has the bigger context window?
Both accept 200K tokens.
How many benchmarks do Claude Haiku 4.5 and GLM-4.7-Flash share?
20 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and GLM-4.7-Flash has 21.