Model comparison
GPT-5.3 Chat vs Llama 4 Maverick
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 30.9 on the Noometry Index. Llama 4 Maverick costs 16× 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 4 Maverick in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 38.8.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Chat | Llama 4 Maverick | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 42.8 | 30.9 |
| Released | 2026-03-03 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 128K | 128K |
| Max output | 16K | 4K |
| Input $ / M tokens | $1.75 | $0.19 |
| Output $ / M tokens | $14 | $0.65 |
| Results tracked | 18 | 54 |
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Category by category
Coding GPT-5.3 Chat leads
GPT-5.3 Chat: 41.4 (#124), Llama 4 Maverick: 26.6 (#324)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Coding | 1408 | 1302 |
| SWE-bench Verified (bash only) | — | 21% |
| Aider Polyglot | — | 15.6% |
| SciCode | — | 33.1% |
| WeirdML | — | 24.5% |
| BigCodeBench Instruct | — | 49.7% |
| BigCodeBench Complete | — | 61.4% |
| ALE-Bench | — | 172.97 |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, Llama 4 Maverick: 28.2 (#91)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.3% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 28.5 (#102), Llama 4 Maverick: 10.1 (#342)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1281 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | — | 27.7% |
| Kagi LLM Benchmark | — | 55.9% |
| NYT Connections (extended) | — | 8% |
| ARC-AGI-1 | — | 4.4% |
| CritPt | — | 0% |
| EnigmaEval | — | 0.6% |
| DTBench | — | 61.9% |
| LMCA | — | 15.9% |
| Epoch Capabilities Index | — | 132.2 |
| ForecastBench | — | 57.5 |
Math GPT-5.3 Chat leads
GPT-5.3 Chat: 38.2 (#142), Llama 4 Maverick: 26.0 (#262)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Math | 1389 | 1299 |
| OTIS Mock AIME 2024-2025 | — | 20.6% |
| Omni-MATH | — | 42.2% |
| MATH Level 5 | — | 73% |
| FrontierMath (Feb 2025 set) | — | 0.7% |
Knowledge GPT-5.3 Chat leads
GPT-5.3 Chat: 38.8 (#140), Llama 4 Maverick: 33.4 (#204)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Expert | 1397 | 1259 |
| GPQA Diamond | — | 67% |
| Humanity's Last Exam | — | 5.7% |
| MMLU-Pro | — | 81% |
| Confabulations | — | 22.6% |
| Vectara Hallucination Rate | — | 8.2% |
| GPQA (HELM) | — | 65% |
Multimodal Not comparable
GPT-5.3 Chat: —, Llama 4 Maverick: 31.6 (#105)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Vision | — | 1142 |
| GeoBench | — | 52% |
| SpatialViz-Bench | — | 31.8% |
Multilingual GPT-5.3 Chat leads
GPT-5.3 Chat: 50.3 (#124), Llama 4 Maverick: 42.2 (#195)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Non-English | 1382 | 1269 |
| LMArena Chinese | 1432 | 1277 |
| LMArena French | 1397 | 1259 |
| LMArena German | 1384 | 1291 |
| LMArena Japanese | 1352 | 1207 |
| LMArena Korean | 1346 | 1203 |
| LMArena Russian | 1400 | 1286 |
| LMArena Spanish | 1371 | 1293 |
Instruction Following GPT-5.3 Chat leads
GPT-5.3 Chat: 72.8 (#129), Llama 4 Maverick: 71.7 (#146)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Instruction Following | 1378 | 1267 |
| IFEval | — | 90.8% |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#120), Llama 4 Maverick: 31.4 (#279)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Longer Query | 1396 | 1280 |
| Fiction.LiveBench | — | 46.2% |
Writing & Preference GPT-5.3 Chat leads
GPT-5.3 Chat: 63.1 (#68), Llama 4 Maverick: 38.8 (#252)
| Benchmark | GPT-5.3 Chat | Llama 4 Maverick |
|---|---|---|
| LMArena Text | 1389 | 1287 |
| LMArena Creative Writing | 1355 | 1267 |
| EQ-Bench Creative Writing | 1690 | 860 |
| LMArena Multi-Turn | 1412 | 1289 |
| Short-Story Creative Writing | — | 62% |
| WildBench | — | 80% |
Frequently asked questions
Is GPT-5.3 Chat better than Llama 4 Maverick?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 30.9 on the Noometry Index. Llama 4 Maverick costs 16× 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 4 Maverick?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or Llama 4 Maverick better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 26.6 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 4 Maverick share?
18 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Llama 4 Maverick has 54.