Noometry

Model comparison

GPT-6 Astra vs Llama-3.3-70B-Instruct

GPT-6 Astra is the stronger model overall, scoring 70.8 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 129× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

Last verified . 27 shared benchmarks.

GPT-6 Astra OpenAI

70.8

Rank #1 Confirmed

Llama-3.3-70B-Instruct Meta

30.6

Rank #291 Confirmed

Summary

  • They share 27 benchmarks with published results for both. GPT-6 Astra scores higher in 9 categories and Llama-3.3-70B-Instruct in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-6 Astra leads 93.5 to 15.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for GPT-6 Astra and 5.1% for Llama-3.3-70B-Instruct.
  • Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
  • GPT-6 Astra accepts more context: 1.05M tokens versus 128K.
  • Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

Side by side

GPT-6 AstraLlama-3.3-70B-Instruct
ProviderOpenAIMeta
Noometry Index70.830.6
Released2026-09-032024-12-06
WeightsProprietaryOpen
Context window1.05M128K
Max output128K4K
Input $ / M tokens$10$0.10
Output $ / M tokens$50$0.32
Results tracked5643

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Category by category

Coding GPT-6 Astra leads

GPT-6 Astra: 73.7 (#2), Llama-3.3-70B-Instruct: 31.0 (#290)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
SciCode56.5%26%
WeirdML93.6%14.4%
LMArena Coding14871268
DeepSWE74.1%—
FrontierCode53.3%—
LMArena WebDev1786—
FrontierSWE65.5%—
GSO79.4%—
BigCodeBench Instruct—46.9%
LiveBench Coding—36.6%
MirrorCode46.7%—
BigCodeBench Complete—57.5%
ALE-Bench2,951—

Agentic & Tool Use GPT-6 Astra leads

GPT-6 Astra: 52.9 (#3), Llama-3.3-70B-Instruct: 25.8 (#105)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
BALROG68.3%23%
APEX-Agents64.7%—
Berkeley Function Calling Leaderboard—31.9%
Remote Labor Index20.8%—
GDP.pdf34.2%—
Vending-Bench 215,515—

Reasoning GPT-6 Astra leads

GPT-6 Astra: 85.1 (#1), Llama-3.3-70B-Instruct: 14.1 (#327)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
CritPt31.7%0%
LMArena Hard Prompts14621257
DTBench97.3%59.5%
LMCA64.4%17.5%
Epoch Capabilities Index166.45127.33
ARC-AGI-295%—
SimpleBench—19.9%
NYT Connections (extended)98.1%—
ARC-AGI-198.5%—
Chess Puzzles72%—
EBR-Bench76.2%—
LiveBench Reasoning—50.8%
Mystery Game Puzzles84%—
LiveBench Data Analysis—49.5%
Bench to the Future 30.14—
ForecastBench—58.6
LiveBench—50.2%

Math GPT-6 Astra leads

GPT-6 Astra: 93.5 (#2), Llama-3.3-70B-Instruct: 15.3 (#298)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
OTIS Mock AIME 2024-2025100%5.1%
LMArena Math14651267
FrontierMath (Tiers 1-3)93.7%—
FrontierMath Tier 497.6%—
ProofBench99%—
LiveBench Math—42.2%
MATH Level 5—41.6%
FrontierMath Erdős2.9%—

Knowledge GPT-6 Astra leads

GPT-6 Astra: 75.3 (#1), Llama-3.3-70B-Instruct: 30.6 (#226)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
GPQA Diamond95.8%47.4%
Vectara Hallucination Rate8.7%4.1%
LMArena Expert14831225
Humanity's Last Exam54.8%—
SimpleQA Verified75.6%—
Confabulations—22.8%
MMLU—86.3%

Multimodal Not comparable

GPT-6 Astra: 55.0 (#3), Llama-3.3-70B-Instruct: —

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
LMArena Vision1281—
Blueprint-Bench 249.7%—
Furniture Assembly80%—
LMArena Document1468—

Multilingual GPT-6 Astra leads

GPT-6 Astra: 53.7 (#61), Llama-3.3-70B-Instruct: 39.9 (#220)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
LMArena Non-English14301236
LMArena Chinese14841217
LMArena French14561281
LMArena German14401251
LMArena Japanese13791150
LMArena Korean14261143
LMArena Russian14361252
LMArena Spanish14071270

Instruction Following GPT-6 Astra leads

GPT-6 Astra: 76.3 (#44), Llama-3.3-70B-Instruct: 71.1 (#157)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
LMArena Instruction Following14501242
LiveBench Instruction Following—82.7%

Long Context GPT-6 Astra leads

GPT-6 Astra: 44.5 (#62), Llama-3.3-70B-Instruct: 26.4 (#295)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
LMArena Longer Query14561256
Fiction.LiveBench—33.3%

Writing & Preference GPT-6 Astra leads

GPT-6 Astra: 75.3 (#7), Llama-3.3-70B-Instruct: 47.6 (#207)

BenchmarkGPT-6 AstraLlama-3.3-70B-Instruct
LMArena Text14411274
LMArena Creative Writing14181250
LMArena Multi-Turn14481280
EQ-Bench Creative Writing2173—
LiveBench Language—39.2%

Frequently asked questions

Is GPT-6 Astra better than Llama-3.3-70B-Instruct?

GPT-6 Astra is the stronger model overall, scoring 70.8 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 129× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

Which is cheaper, GPT-6 Astra 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-6 Astra lists at $10 and $50.

Is GPT-6 Astra or Llama-3.3-70B-Instruct better for coding?

GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 31.0 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Astra does, with 1.05M tokens against 128K.

How many benchmarks do GPT-6 Astra and Llama-3.3-70B-Instruct share?

27 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Llama-3.3-70B-Instruct has 43.

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