Noometry

Model comparison

GPT-5.3 Chat vs Llama 3.1-70B

GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 29.6 on the Noometry Index. Llama 3.1-70B costs 12× 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.

GPT-5.3 Chat OpenAI

42.8

Rank #109 Confirmed

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Llama 3.1-70B 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 35.4.
  • Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • Llama 3.1-70B has downloadable open weights; the other is API-only.

Side by side

GPT-5.3 ChatLlama 3.1-70B
ProviderOpenAIMeta
Noometry Index42.829.6
Released2026-03-032024-07-23
WeightsProprietaryOpen
Context window128K128K
Max output16K4K
Input $ / M tokens$1.75$0.40
Output $ / M tokens$14$0.40
Results tracked1835

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Category by category

Coding GPT-5.3 Chat leads

GPT-5.3 Chat: 41.4 (#124), Llama 3.1-70B: 30.3 (#296)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Coding14081260
WeirdML—9%
BigCodeBench Instruct—46.1%
BigCodeBench Complete—54.8%

Agentic & Tool Use Not comparable

GPT-5.3 Chat: —, Llama 3.1-70B: 25.1 (#112)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
TheAgentCompany—6.9%
BALROG—27.9%

Reasoning GPT-5.3 Chat leads

GPT-5.3 Chat: 28.5 (#102), Llama 3.1-70B: 21.6 (#220)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Hard Prompts13991241
DTBench—60%
LMCA—14.8%
Epoch Capabilities Index—125.92

Math GPT-5.3 Chat leads

GPT-5.3 Chat: 38.2 (#142), Llama 3.1-70B: 13.5 (#304)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Math13891252
OTIS Mock AIME 2024-2025—3.6%
Omni-MATH—21%
MATH Level 5—36.7%

Knowledge GPT-5.3 Chat leads

GPT-5.3 Chat: 38.8 (#140), Llama 3.1-70B: 24.2 (#269)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Expert13971209
GPQA Diamond—44.2%
MMLU-Pro—65.3%
GPQA (HELM)—42.6%
MMLU—80.1%

Multilingual GPT-5.3 Chat leads

GPT-5.3 Chat: 50.3 (#124), Llama 3.1-70B: 38.8 (#225)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Non-English13821219
LMArena Chinese14321215
LMArena French13971261
LMArena German13841222
LMArena Japanese13521132
LMArena Korean13461140
LMArena Russian14001234
LMArena Spanish13711253

Instruction Following GPT-5.3 Chat leads

GPT-5.3 Chat: 72.8 (#129), Llama 3.1-70B: 65.3 (#223)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Instruction Following13781231
IFEval—82.1%

Long Context GPT-5.3 Chat leads

GPT-5.3 Chat: 42.6 (#120), Llama 3.1-70B: 37.6 (#214)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Longer Query13961241

Writing & Preference GPT-5.3 Chat leads

GPT-5.3 Chat: 63.1 (#68), Llama 3.1-70B: 35.4 (#267)

BenchmarkGPT-5.3 ChatLlama 3.1-70B
LMArena Text13891261
LMArena Creative Writing13551232
EQ-Bench Creative Writing1690784
LMArena Multi-Turn14121256
WildBench—75.8%

Frequently asked questions

Is GPT-5.3 Chat better than Llama 3.1-70B?

GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 29.6 on the Noometry Index. Llama 3.1-70B costs 12× 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 3.1-70B?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

Is GPT-5.3 Chat or Llama 3.1-70B better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 30.3 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 3.1-70B share?

18 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Llama 3.1-70B has 35.

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