Model comparison
GLM-4.7 vs Laguna M.1
GLM-4.7 is the stronger model overall, scoring 42.0 to 32.5 on the Noometry Index.
Last verified . 2 shared benchmarks.
PoolsideSummary
- They share 2 benchmarks with published results for both. GLM-4.7 scores higher in 3 categories and Laguna M.1 in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.7 leads 38.6 to 21.1.
- The biggest single-benchmark swing is ProofBench: 6% for GLM-4.7 and 0% for Laguna M.1.
- Laguna M.1 accepts more context: 262K tokens versus 205K.
Side by side
| GLM-4.7 | Laguna M.1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Poolside |
| Noometry Index | 42.0 | 32.5 |
| Released | 2025-12-22 | 2026-04-28 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 33K |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 36 | 3 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), Laguna M.1: 36.6 (#204)
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| LMArena WebDev | 1435 | 1349 |
| SciCode | 45.1% | — |
| LMArena Coding | 1454 | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.5 (#103), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 24.3 (#164), Laguna M.1: 23.1 (#184)
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| LMArena Hard Prompts | 1443 | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 143.51 | — |
Math GLM-4.7 leads
GLM-4.7: 38.6 (#135), Laguna M.1: 21.1 (#283)
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| ProofBench | 6% | 0% |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| LMArena Math | 1423 | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Not comparable
GLM-4.7: 47.0 (#80), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| LMArena Expert | 1424 | — |
Multilingual Not comparable
GLM-4.7: 52.8 (#79), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1432 | — |
| LMArena German | 1424 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1399 | — |
| LMArena Russian | 1423 | — |
| LMArena Spanish | 1434 | — |
Instruction Following Not comparable
GLM-4.7: 74.4 (#95), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| LMArena Instruction Following | 1411 | — |
Long Context Not comparable
GLM-4.7: 42.8 (#116), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
| LMArena Longer Query | 1432 | — |
Writing & Preference Not comparable
GLM-4.7: 60.9 (#93), Laguna M.1: —
| Benchmark | GLM-4.7 | Laguna M.1 |
|---|---|---|
| LMArena Text | 1435 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1413 | — |
| LMArena Multi-Turn | 1446 | — |
Frequently asked questions
Is GLM-4.7 better than Laguna M.1?
GLM-4.7 is the stronger model overall, scoring 42.0 to 32.5 on the Noometry Index.
Is GLM-4.7 or Laguna M.1 better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 36.6 in the Noometry coding category.
Which has the bigger context window?
Laguna M.1 does, with 262K tokens against 205K.
How many benchmarks do GLM-4.7 and Laguna M.1 share?
2 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Laguna M.1 has 3.