Model comparison
Gemma 3 27B vs GLM-4.7-Flash
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.8 on the Noometry Index.
Last verified . 21 shared benchmarks.
GoogleSummary
- They share 21 benchmarks with published results for both. Gemma 3 27B scores higher in 3 categories and GLM-4.7-Flash in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7-Flash leads 40.6 to 22.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 22.5% for Gemma 3 27B and 58.3% for GLM-4.7-Flash.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
- GLM-4.7-Flash accepts more context: 200K tokens versus 131K.
Side by side
| Gemma 3 27B | GLM-4.7-Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 30.8 | 38.8 |
| Released | 2025-03-11 | 2026-01-19 |
| Weights | Open | Open |
| Context window | 131K | 200K |
| Max output | 8K | 131K |
| Input $ / M tokens | $0.08 | $0.06 |
| Output $ / M tokens | $0.16 | $0.40 |
| Results tracked | 43 | 21 |
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Category by category
Coding GLM-4.7-Flash leads
Gemma 3 27B: 22.5 (#334), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1322 | 1383 |
| Aider Polyglot | 4.9% | — |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
Agentic & Tool Use Not comparable
Gemma 3 27B: 25.1 (#110), GLM-4.7-Flash: —
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
Reasoning GLM-4.7-Flash leads
Gemma 3 27B: 16.7 (#301), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| LMArena Hard Prompts | 1340 | 1356 |
| Kagi LLM Benchmark | 40.4% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 43.8% | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| Epoch Capabilities Index | 130.04 | — |
| LiveBench | 50% | — |
Math GLM-4.7-Flash leads
Gemma 3 27B: 25.9 (#265), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | 58.3% |
| LMArena Math | 1312 | 1355 |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
Knowledge GLM-4.7-Flash leads
Gemma 3 27B: 25.5 (#261), GLM-4.7-Flash: 35.5 (#184)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | 47.7% | 60.5% |
| Vectara Hallucination Rate | 7.4% | 9.3% |
| LMArena Expert | 1304 | 1357 |
| Confabulations | 40.3% | — |
Multimodal Not comparable
Gemma 3 27B: 32.6 (#100), GLM-4.7-Flash: —
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Vision | 1164 | — |
| GeoBench | 52% | — |
Multilingual Too close to call
Gemma 3 27B: 46.9 (#155), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1334 | 1330 |
| LMArena Chinese | 1346 | 1403 |
| LMArena French | 1368 | 1332 |
| LMArena German | 1362 | 1337 |
| LMArena Korean | 1308 | 1283 |
| LMArena Russian | 1349 | 1332 |
| LMArena Spanish | 1349 | 1350 |
| LMArena Japanese | 1287 | — |
Instruction Following Too close to call
Gemma 3 27B: 70.6 (#160), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1321 | 1327 |
| LiveBench Instruction Following | 74.9% | — |
Long Context GLM-4.7-Flash leads
Gemma 3 27B: 27.6 (#293), GLM-4.7-Flash: 40.9 (#148)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1333 | 1345 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Gemma 3 27B leads
Gemma 3 27B: 52.5 (#168), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | Gemma 3 27B | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1358 | 1351 |
| LMArena Creative Writing | 1346 | 1297 |
| EQ-Bench Creative Writing | 1266 | 1125 |
| LMArena Multi-Turn | 1345 | 1342 |
| Short-Story Creative Writing | 79.9% | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GLM-4.7-Flash?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.8 on the Noometry Index.
Which is cheaper, Gemma 3 27B or GLM-4.7-Flash?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.
Is Gemma 3 27B or GLM-4.7-Flash better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 131K.
How many benchmarks do Gemma 3 27B and GLM-4.7-Flash share?
21 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and GLM-4.7-Flash has 21.