Model comparison
Codellama 70b Instruct vs GPT-5.3 Chat
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 33.7 on the Noometry Index.
Last verified . 4 shared benchmarks.
MetaSummary
- They share 4 benchmarks with published results for both. Codellama 70b Instruct scores higher in 0 categories and GPT-5.3 Chat in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 33.4.
- Codellama 70b Instruct has downloadable open weights; the other is API-only.
Side by side
| Codellama 70b Instruct | GPT-5.3 Chat | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 33.7 | 42.8 |
| Released | — | 2026-03-03 |
| Weights | Open | Proprietary |
| Context window | — | 128K |
| Max output | — | 16K |
| Input $ / M tokens | — | $1.75 |
| Output $ / M tokens | — | $14 |
| Results tracked | 7 | 18 |
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Category by category
Coding GPT-5.3 Chat leads
Codellama 70b Instruct: 37.6 (#193), GPT-5.3 Chat: 41.4 (#124)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| BigCodeBench Instruct | 40.7% | — |
| LMArena Coding | — | 1408 |
| BigCodeBench Complete | 49.6% | — |
| HumanEval+ | 65.9% | — |
Reasoning GPT-5.3 Chat leads
Codellama 70b Instruct: 20.1 (#242), GPT-5.3 Chat: 28.5 (#102)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 1052 | 1399 |
Math Not comparable
Codellama 70b Instruct: —, GPT-5.3 Chat: 38.2 (#142)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | — | 1389 |
Knowledge Not comparable
Codellama 70b Instruct: —, GPT-5.3 Chat: 38.8 (#140)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | — | 1397 |
Multilingual GPT-5.3 Chat leads
Codellama 70b Instruct: 24.8 (#288), GPT-5.3 Chat: 50.3 (#124)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 992 | 1382 |
| LMArena Chinese | — | 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
Codellama 70b Instruct: 51.9 (#293), GPT-5.3 Chat: 72.8 (#129)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 1024 | 1378 |
Long Context Not comparable
Codellama 70b Instruct: —, GPT-5.3 Chat: 42.6 (#120)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | — | 1396 |
Writing & Preference GPT-5.3 Chat leads
Codellama 70b Instruct: 33.4 (#277), GPT-5.3 Chat: 63.1 (#68)
| Benchmark | Codellama 70b Instruct | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 1057 | 1389 |
| LMArena Creative Writing | — | 1355 |
| EQ-Bench Creative Writing | — | 1690 |
| LMArena Multi-Turn | — | 1412 |
Frequently asked questions
Is Codellama 70b Instruct better than GPT-5.3 Chat?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 33.7 on the Noometry Index.
Is Codellama 70b Instruct or GPT-5.3 Chat better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 37.6 in the Noometry coding category.
How many benchmarks do Codellama 70b Instruct and GPT-5.3 Chat share?
4 benchmarks have published results for both models. Codellama 70b Instruct has 7 scored results on Noometry and GPT-5.3 Chat has 18.