Model comparison
GLM-5.3 vs OLMo 2 Furious 13B
GLM-5.3 is the stronger model overall, scoring 54.8 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-5.3 leads 58.3 to 18.3.
Side by side
| GLM-5.3 | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 54.8 | 29.7 |
| Released | 2026-08-14 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $1.40 | — |
| Output $ / M tokens | $4.40 | — |
| Results tracked | 42 | 12 |
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Category by category
Coding GLM-5.3 leads
GLM-5.3: 59.5 (#14), OLMo 2 Furious 13B: 28.6 (#313)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| CursorBench | 42.6% | — |
| LMArena WebDev | 1622 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| WeirdML | 75.4% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1496 | — |
| ALE-Bench | 1,317 | — |
Agentic & Tool Use Not comparable
GLM-5.3: 36.4 (#38), OLMo 2 Furious 13B: —
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Vending-Bench 2 | 8,164 | — |
Reasoning GLM-5.3 leads
GLM-5.3: 46.1 (#46), OLMo 2 Furious 13B: 15.5 (#314)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| NYT Connections (extended) | 74.2% | — |
| CritPt | 19.1% | — |
| Chess Puzzles | 21% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1489 | — |
| Mystery Game Puzzles | 33% | — |
| DTBench | 87.7% | — |
| LiveBench Data Analysis | — | 20.6% |
| LMCA | 55.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 155.61 | — |
| LiveBench | — | 22.1% |
Math GLM-5.3 leads
GLM-5.3: 62.3 (#33), OLMo 2 Furious 13B: 23.1 (#273)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 91.1% | — |
| ProofBench | 49% | — |
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1489 | — |
Knowledge GLM-5.3 leads
GLM-5.3: 58.3 (#37), OLMo 2 Furious 13B: 18.3 (#283)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| GPQA Diamond | 90.9% | — |
| SimpleQA Verified | 41% | — |
| MMLU-Pro | — | 31% |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1516 | — |
Multilingual Not comparable
GLM-5.3: 55.7 (#28), OLMo 2 Furious 13B: —
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1457 | — |
| LMArena Chinese | 1528 | — |
| LMArena French | 1499 | — |
| LMArena German | 1499 | — |
| LMArena Japanese | 1453 | — |
| LMArena Korean | 1472 | — |
| LMArena Russian | 1463 | — |
| LMArena Spanish | 1460 | — |
Instruction Following GLM-5.3 leads
GLM-5.3: 77.5 (#23), OLMo 2 Furious 13B: 60.9 (#248)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1477 | — |
Long Context Not comparable
GLM-5.3: 45.4 (#41), OLMo 2 Furious 13B: —
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Longer Query | 1482 | — |
Writing & Preference GLM-5.3 leads
GLM-5.3: 75.7 (#6), OLMo 2 Furious 13B: 42.9 (#230)
| Benchmark | GLM-5.3 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1471 | — |
| LMArena Creative Writing | 1457 | — |
| EQ-Bench Creative Writing | 2075 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1472 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is GLM-5.3 better than OLMo 2 Furious 13B?
GLM-5.3 is the stronger model overall, scoring 54.8 to 29.7 on the Noometry Index.
Is GLM-5.3 or OLMo 2 Furious 13B better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 versus 28.6 in the Noometry coding category.
How many benchmarks do GLM-5.3 and OLMo 2 Furious 13B share?
0 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and OLMo 2 Furious 13B has 12.