Model comparison
Dolly 2.0-12b vs GLM-4.7-Flash
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 25.5 on the Noometry Index.
Last verified . 9 shared benchmarks.
DatabricksSummary
- They share 9 benchmarks with published results for both. Dolly 2.0-12b scores higher in 0 categories and GLM-4.7-Flash in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.7-Flash leads 47.4 to 15.2.
Side by side
| Dolly 2.0-12b | GLM-4.7-Flash | |
|---|---|---|
| Provider | Databricks | Z.ai (Zhipu) |
| Noometry Index | 25.5 | 38.8 |
| Released | 2023-04-11 | 2026-01-19 |
| Weights | Open | Open |
| Context window | — | 200K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.06 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 17 | 21 |
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Category by category
Coding GLM-4.7-Flash leads
Dolly 2.0-12b: 23.4 (#332), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 776 | 1383 |
Reasoning GLM-4.7-Flash leads
Dolly 2.0-12b: 15.3 (#316), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Hard Prompts | 804 | 1356 |
| Chess Puzzles | — | 0% |
| Epoch Capabilities Index | 89.67 | — |
| HellaSwag | 70.8% | — |
| PIQA | 75.4% | — |
| WinoGrande | 61.8% | — |
Math GLM-4.7-Flash leads
Dolly 2.0-12b: 27.3 (#251), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Math | 871 | 1355 |
| OTIS Mock AIME 2024-2025 | — | 58.3% |
Knowledge Not comparable
Dolly 2.0-12b: —, GLM-4.7-Flash: 35.5 (#184)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | — | 60.5% |
| Vectara Hallucination Rate | — | 9.3% |
| LMArena Expert | — | 1357 |
| ARC (AI2) Challenge | 39.6% | — |
| BoolQ | 56.3% | — |
| MMLU | 26.2% | — |
| OpenBookQA | 39.2% | — |
Multilingual GLM-4.7-Flash leads
Dolly 2.0-12b: 17.4 (#296), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 836 | 1330 |
| LMArena Chinese | 836 | 1403 |
| LMArena French | — | 1332 |
| LMArena German | — | 1337 |
| LMArena Korean | — | 1283 |
| LMArena Russian | — | 1332 |
| LMArena Spanish | — | 1350 |
Instruction Following GLM-4.7-Flash leads
Dolly 2.0-12b: 38.7 (#304), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 814 | 1327 |
Long Context Not comparable
Dolly 2.0-12b: —, GLM-4.7-Flash: 40.9 (#148)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | — | 1345 |
Writing & Preference GLM-4.7-Flash leads
Dolly 2.0-12b: 15.2 (#311), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | Dolly 2.0-12b | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 851 | 1351 |
| LMArena Creative Writing | 864 | 1297 |
| LMArena Multi-Turn | 740 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |
Frequently asked questions
Is Dolly 2.0-12b better than GLM-4.7-Flash?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 25.5 on the Noometry Index.
Is Dolly 2.0-12b or GLM-4.7-Flash better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 23.4 in the Noometry coding category.
How many benchmarks do Dolly 2.0-12b and GLM-4.7-Flash share?
9 benchmarks have published results for both models. Dolly 2.0-12b has 17 scored results on Noometry and GLM-4.7-Flash has 21.