Model comparison
GLM-4.6 vs OLMo 2 Furious 13B
GLM-4.6 is the stronger model overall, scoring 41.4 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-4.6 leads 40.2 to 18.3.
Side by side
| GLM-4.6 | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 41.4 | 29.7 |
| Released | 2025-09-30 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 12 |
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Category by category
Coding GLM-4.6 leads
GLM-4.6: 40.1 (#148), OLMo 2 Furious 13B: 28.6 (#313)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.3 (#66), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning GLM-4.6 leads
GLM-4.6: 23.7 (#172), OLMo 2 Furious 13B: 15.5 (#314)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1440 | — |
| LiveBench Data Analysis | — | 20.6% |
| LiveBench | — | 22.1% |
Math GLM-4.6 leads
GLM-4.6: 39.1 (#111), OLMo 2 Furious 13B: 23.1 (#273)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1432 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 40.2 (#124), OLMo 2 Furious 13B: 18.3 (#283)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| MMLU-Pro | — | 31% |
| Vectara Hallucination Rate | 9.5% | — |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1431 | — |
Multilingual Not comparable
GLM-4.6: 53.5 (#66), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1499 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Russian | 1419 | — |
| LMArena Spanish | 1436 | — |
Instruction Following GLM-4.6 leads
GLM-4.6: 74.3 (#98), OLMo 2 Furious 13B: 60.9 (#248)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1410 | — |
Long Context Not comparable
GLM-4.6: 43.4 (#94), OLMo 2 Furious 13B: —
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Longer Query | 1422 | — |
Writing & Preference GLM-4.6 leads
GLM-4.6: 61.1 (#90), OLMo 2 Furious 13B: 42.9 (#230)
| Benchmark | GLM-4.6 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| EQ-Bench Creative Writing | 1411 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1427 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is GLM-4.6 better than OLMo 2 Furious 13B?
GLM-4.6 is the stronger model overall, scoring 41.4 to 29.7 on the Noometry Index.
Is GLM-4.6 or OLMo 2 Furious 13B better for coding?
GLM-4.6 scores higher on coding benchmarks: 40.1 versus 28.6 in the Noometry coding category.
How many benchmarks do GLM-4.6 and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and OLMo 2 Furious 13B has 12.