Model comparison
GPT-5.3 Chat vs Llama 3.1-8B
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 22.8 on the Noometry Index. Llama 3.1-8B costs 84× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
MetaSummary
- They share 18 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Llama 3.1-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.3 to 29.9.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Llama 3.1-8B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Chat | Llama 3.1-8B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 42.1 | 22.8 |
| Released | 2026-03-03 | 2024-07-23 |
| Weights | Proprietary | Open |
| Context window | 128K | 128K |
| Max output | 16K | 4K |
| Input $ / M tokens | $1.75 | $0.05 |
| Output $ / M tokens | $14 | $0.08 |
| Results tracked | 18 | 43 |
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Category by category
Coding GPT-5.3 Chat leads
GPT-5.3 Chat: 40.8 (#124), Llama 3.1-8B: 19.9 (#335)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Coding | 1408 | 1195 |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, Llama 3.1-8B: 22.3 (#123)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 27.3 (#105), Llama 3.1-8B: 14.5 (#316)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1175 |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.48 |
| PIQA | — | 81.2% |
Math GPT-5.3 Chat leads
GPT-5.3 Chat: 35.4 (#146), Llama 3.1-8B: 9.5 (#311)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1389 | 1179 |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |
Knowledge GPT-5.3 Chat leads
GPT-5.3 Chat: 38.2 (#137), Llama 3.1-8B: 8.0 (#302)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1397 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |
Multilingual GPT-5.3 Chat leads
GPT-5.3 Chat: 50.5 (#119), Llama 3.1-8B: 34.2 (#244)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1383 | 1148 |
| LMArena Chinese | 1433 | 1151 |
| LMArena French | 1398 | 1176 |
| LMArena German | 1384 | 1144 |
| LMArena Japanese | 1351 | 1061 |
| LMArena Korean | 1347 | 1053 |
| LMArena Russian | 1400 | 1158 |
| LMArena Spanish | 1371 | 1169 |
Instruction Following GPT-5.3 Chat leads
GPT-5.3 Chat: 73.0 (#124), Llama 3.1-8B: 59.1 (#253)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1378 | 1159 |
| IFEval | — | 74.3% |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#115), Llama 3.1-8B: 35.8 (#233)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1396 | 1182 |
Writing & Preference GPT-5.3 Chat leads
GPT-5.3 Chat: 63.3 (#65), Llama 3.1-8B: 29.9 (#285)
| Benchmark | GPT-5.3 Chat | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1389 | 1187 |
| LMArena Creative Writing | 1356 | 1154 |
| EQ-Bench Creative Writing | 1690 | 713 |
| LMArena Multi-Turn | 1413 | 1172 |
| WildBench | — | 68.7% |
Frequently asked questions
Is GPT-5.3 Chat better than Llama 3.1-8B?
GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 22.8 on the Noometry Index. Llama 3.1-8B costs 84× 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 3.1-8B?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or Llama 3.1-8B better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 19.9 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 3.1-8B share?
18 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Llama 3.1-8B has 43.