Model comparison
Dolly 2.0-12b vs GPT-5.3 Chat
GPT-5.3 Chat is the stronger model overall, scoring 42.8 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 GPT-5.3 Chat in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 15.2.
- Dolly 2.0-12b has downloadable open weights; the other is API-only.
Side by side
| Dolly 2.0-12b | GPT-5.3 Chat | |
|---|---|---|
| Provider | Databricks | OpenAI |
| Noometry Index | 25.5 | 42.8 |
| Released | 2023-04-11 | 2026-03-03 |
| Weights | Open | Proprietary |
| Context window | — | 128K |
| Max output | — | 16K |
| Input $ / M tokens | — | $1.75 |
| Output $ / M tokens | — | $14 |
| Results tracked | 17 | 18 |
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Category by category
Coding GPT-5.3 Chat leads
Dolly 2.0-12b: 23.4 (#332), GPT-5.3 Chat: 41.4 (#124)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Coding | 776 | 1408 |
Reasoning GPT-5.3 Chat leads
Dolly 2.0-12b: 15.3 (#316), GPT-5.3 Chat: 28.5 (#102)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 804 | 1399 |
| Epoch Capabilities Index | 89.67 | — |
| HellaSwag | 70.8% | — |
| PIQA | 75.4% | — |
| WinoGrande | 61.8% | — |
Math GPT-5.3 Chat leads
Dolly 2.0-12b: 27.3 (#251), GPT-5.3 Chat: 38.2 (#142)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | 871 | 1389 |
Knowledge Not comparable
Dolly 2.0-12b: —, GPT-5.3 Chat: 38.8 (#140)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | — | 1397 |
| ARC (AI2) Challenge | 39.6% | — |
| BoolQ | 56.3% | — |
| MMLU | 26.2% | — |
| OpenBookQA | 39.2% | — |
Multilingual GPT-5.3 Chat leads
Dolly 2.0-12b: 17.4 (#296), GPT-5.3 Chat: 50.3 (#124)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 836 | 1382 |
| LMArena Chinese | 836 | 1432 |
| LMArena French | — | 1397 |
| LMArena German | — | 1384 |
| LMArena Japanese | — | 1352 |
| LMArena Korean | — | 1346 |
| LMArena Russian | — | 1400 |
| LMArena Spanish | — | 1371 |
Instruction Following GPT-5.3 Chat leads
Dolly 2.0-12b: 38.7 (#304), GPT-5.3 Chat: 72.8 (#129)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 814 | 1378 |
Long Context Not comparable
Dolly 2.0-12b: —, GPT-5.3 Chat: 42.6 (#120)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | — | 1396 |
Writing & Preference GPT-5.3 Chat leads
Dolly 2.0-12b: 15.2 (#311), GPT-5.3 Chat: 63.1 (#68)
| Benchmark | Dolly 2.0-12b | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 851 | 1389 |
| LMArena Creative Writing | 864 | 1355 |
| LMArena Multi-Turn | 740 | 1412 |
| EQ-Bench Creative Writing | — | 1690 |
Frequently asked questions
Is Dolly 2.0-12b better than GPT-5.3 Chat?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 25.5 on the Noometry Index.
Is Dolly 2.0-12b or GPT-5.3 Chat better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 23.4 in the Noometry coding category.
How many benchmarks do Dolly 2.0-12b and GPT-5.3 Chat share?
9 benchmarks have published results for both models. Dolly 2.0-12b has 17 scored results on Noometry and GPT-5.3 Chat has 18.