Model comparison
GLM-4.7-Flash vs Olmo 3.1 32b Think
GLM-4.7-Flash and Olmo 3.1 32b Think score almost the same on the Noometry Index (38.8 vs 37.9), so choose on price, context window or the category you care about most.
Last verified . 15 shared benchmarks.
Allen Institute for AI (Ai2)Summary
- They share 15 benchmarks with published results for both. GLM-4.7-Flash scores higher in 5 categories and Olmo 3.1 32b Think in 3 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.7-Flash leads 46.5 to 38.1.
Side by side
| GLM-4.7-Flash | Olmo 3.1 32b Think | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 38.8 | 37.9 |
| Released | 2026-01-19 | — |
| Weights | Open | Open |
| Context window | 200K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.06 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 21 | 15 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Olmo 3.1 32b Think: 37.7 (#189)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Coding | 1383 | 1291 |
Reasoning Olmo 3.1 32b Think leads
GLM-4.7-Flash: 20.9 (#229), Olmo 3.1 32b Think: 25.2 (#150)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1272 |
| Chess Puzzles | 0% | — |
Math Too close to call
GLM-4.7-Flash: 36.1 (#173), Olmo 3.1 32b Think: 36.3 (#168)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Math | 1355 | 1305 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
Knowledge Too close to call
GLM-4.7-Flash: 35.5 (#184), Olmo 3.1 32b Think: 35.7 (#181)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Expert | 1357 | 1295 |
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Olmo 3.1 32b Think: 38.1 (#231)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Non-English | 1330 | 1209 |
| LMArena Chinese | 1403 | 1242 |
| LMArena French | 1332 | 1260 |
| LMArena German | 1337 | 1262 |
| LMArena Russian | 1332 | 1193 |
| LMArena Spanish | 1350 | 1289 |
| LMArena Korean | 1283 | — |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Olmo 3.1 32b Think: 65.6 (#218)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Instruction Following | 1327 | 1247 |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Olmo 3.1 32b Think: 38.6 (#195)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Longer Query | 1345 | 1272 |
Writing & Preference GLM-4.7-Flash leads
GLM-4.7-Flash: 47.4 (#210), Olmo 3.1 32b Think: 46.2 (#220)
| Benchmark | GLM-4.7-Flash | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Text | 1351 | 1272 |
| LMArena Creative Writing | 1297 | 1226 |
| LMArena Multi-Turn | 1342 | 1252 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Olmo 3.1 32b Think?
GLM-4.7-Flash and Olmo 3.1 32b Think score almost the same on the Noometry Index (38.8 vs 37.9), so choose on price, context window or the category you care about most.
Is GLM-4.7-Flash or Olmo 3.1 32b Think better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 37.7 in the Noometry coding category.
How many benchmarks do GLM-4.7-Flash and Olmo 3.1 32b Think share?
15 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Olmo 3.1 32b Think has 15.