# GPT-5.3 Chat vs Llama-3.3-70B-Instruct

> GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 31× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-3-chat-vs-llama-3-3-70b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Llama-3.3-70B-Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.3 Chat leads 38.2 to 15.3.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 42.8 | 30.6 |
| Rank | 109 | 291 |
| Context | 128K | 128K |
| Input $/M | $1.75 | $0.10 |
| Output $/M | $14 | $0.32 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.3 Chat: 41.4 (#124)
- Llama-3.3-70B-Instruct: 31.0 (#290)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1408 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |

## Agentic & Tool Use

- GPT-5.3 Chat: —
- Llama-3.3-70B-Instruct: 25.8 (#105)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |

## Reasoning

- GPT-5.3 Chat: 28.5 (#102)
- Llama-3.3-70B-Instruct: 14.1 (#327)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1257 |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| Epoch Capabilities Index | — | 127.33 |
| ForecastBench | — | 58.6 |
| LiveBench | — | 50.2% |

## Math

- GPT-5.3 Chat: 38.2 (#142)
- Llama-3.3-70B-Instruct: 15.3 (#298)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1389 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |

## Knowledge

- GPT-5.3 Chat: 38.8 (#140)
- Llama-3.3-70B-Instruct: 30.6 (#226)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1397 | 1225 |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| MMLU | — | 86.3% |

## Multilingual

- GPT-5.3 Chat: 50.3 (#124)
- Llama-3.3-70B-Instruct: 39.9 (#220)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1382 | 1236 |
| LMArena Chinese | 1432 | 1217 |
| LMArena French | 1397 | 1281 |
| LMArena German | 1384 | 1251 |
| LMArena Japanese | 1352 | 1150 |
| LMArena Korean | 1346 | 1143 |
| LMArena Russian | 1400 | 1252 |
| LMArena Spanish | 1371 | 1270 |

## Instruction Following

- GPT-5.3 Chat: 72.8 (#129)
- Llama-3.3-70B-Instruct: 71.1 (#157)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1378 | 1242 |
| LiveBench Instruction Following | — | 82.7% |

## Long Context

- GPT-5.3 Chat: 42.6 (#120)
- Llama-3.3-70B-Instruct: 26.4 (#295)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1396 | 1256 |
| Fiction.LiveBench | — | 33.3% |

## Writing & Preference

- GPT-5.3 Chat: 63.1 (#68)
- Llama-3.3-70B-Instruct: 47.6 (#207)

| Benchmark | GPT-5.3 Chat | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1389 | 1274 |
| LMArena Creative Writing | 1355 | 1250 |
| LMArena Multi-Turn | 1412 | 1280 |
| EQ-Bench Creative Writing | 1690 | — |
| LiveBench Language | — | 39.2% |

## FAQ

### Is GPT-5.3 Chat better than Llama-3.3-70B-Instruct?

GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 31× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.3 Chat or Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

### Is GPT-5.3 Chat or Llama-3.3-70B-Instruct better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 31.0 in the Noometry coding category.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do GPT-5.3 Chat and Llama-3.3-70B-Instruct share?

17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Llama-3.3-70B-Instruct has 43.