Model comparison
GLM-4.7 vs OLMo 2 Furious 13B
GLM-4.7 is the stronger model overall, scoring 42.0 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Allen Institute for AI (Ai2)Summary
- The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 18.3.
Side by side
| GLM-4.7 | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 42.0 | 29.7 |
| Released | 2025-12-22 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 36 | 12 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), OLMo 2 Furious 13B: 28.6 (#313)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1454 | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Not comparable
GLM-4.7: 26.5 (#103), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 24.3 (#164), OLMo 2 Furious 13B: 15.5 (#314)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1443 | — |
| LiveBench Data Analysis | — | 20.6% |
| Epoch Capabilities Index | 143.51 | — |
| LiveBench | — | 22.1% |
Math GLM-4.7 leads
GLM-4.7: 38.6 (#135), OLMo 2 Furious 13B: 23.1 (#273)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1423 | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GLM-4.7 leads
GLM-4.7: 47.0 (#80), OLMo 2 Furious 13B: 18.3 (#283)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| MMLU-Pro | — | 31% |
| Vectara Hallucination Rate | 11.7% | — |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1424 | — |
Multilingual Not comparable
GLM-4.7: 52.8 (#79), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| 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 GLM-4.7 leads
GLM-4.7: 74.4 (#95), OLMo 2 Furious 13B: 60.9 (#248)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1411 | — |
Long Context Not comparable
GLM-4.7: 42.8 (#116), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
| LMArena Longer Query | 1432 | — |
Writing & Preference GLM-4.7 leads
GLM-4.7: 60.9 (#93), OLMo 2 Furious 13B: 42.9 (#230)
| Benchmark | GLM-4.7 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1435 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1413 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1446 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is GLM-4.7 better than OLMo 2 Furious 13B?
GLM-4.7 is the stronger model overall, scoring 42.0 to 29.7 on the Noometry Index.
Is GLM-4.7 or OLMo 2 Furious 13B better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 28.6 in the Noometry coding category.
How many benchmarks do GLM-4.7 and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and OLMo 2 Furious 13B has 12.