Noometry

Model comparison

Claude Opus 4 vs Llama-3.3-70B-Instruct

Claude Opus 4 is the stronger model overall, scoring 43.1 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 194× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.

Last verified . 30 shared benchmarks.

Claude Opus 4 Anthropic

43.1

Rank #100 Confirmed

Llama-3.3-70B-Instruct Meta

30.6

Rank #291 Confirmed

Summary

  • They share 30 benchmarks with published results for both. Claude Opus 4 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 Claude Opus 4 leads 42.0 to 15.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 64.4% for Claude Opus 4 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 $15 / $75 for Claude Opus 4.
  • Claude Opus 4 accepts more context: 200K tokens versus 128K.
  • Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4Llama-3.3-70B-Instruct
ProviderAnthropicMeta
Noometry Index43.130.6
Released2025-05-222024-12-06
WeightsProprietaryOpen
Context window200K128K
Max output32K4K
Input $ / M tokens$15$0.10
Output $ / M tokens$75$0.32
Results tracked5643

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Category by category

Coding Claude Opus 4 leads

Claude Opus 4: 47.2 (#62), Llama-3.3-70B-Instruct: 31.0 (#290)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
WeirdML43.7%14.4%
LMArena Coding14421268
SWE-bench Verified70.7%—
SWE-bench Verified (bash only)67.6%—
Aider Polyglot72%—
SciCode—26%
GSO6.9%—
BigCodeBench Instruct—46.9%
LiveBench Coding—36.6%
BigCodeBench Complete—57.5%
AlgoTune1.33—

Agentic & Tool Use Claude Opus 4 leads

Claude Opus 4: 34.8 (#42), Llama-3.3-70B-Instruct: 25.8 (#105)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
Berkeley Function Calling Leaderboard—31.9%
Cybench38%—
DeepResearch Bench46.8%—
BALROG—23%
LMArena Search1127—
METR Time Horizons63.9%—

Reasoning Claude Opus 4 leads

Claude Opus 4: 27.3 (#121), Llama-3.3-70B-Instruct: 14.1 (#327)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
SimpleBench58.8%19.9%
CritPt0.3%0%
LMArena Hard Prompts13991257
DTBench81.6%59.5%
LMCA37.4%17.5%
Epoch Capabilities Index142.67127.33
ForecastBench61.158.6
ARC-AGI-28.6%—
Kagi LLM Benchmark74.3%—
ARC-AGI-135.7%—
EnigmaEval5.6%—
LiveBench Reasoning—50.8%
LiveBench Data Analysis—49.5%
LiveBench—50.2%

Math Claude Opus 4 leads

Claude Opus 4: 42.0 (#86), Llama-3.3-70B-Instruct: 15.3 (#298)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
OTIS Mock AIME 2024-202564.4%5.1%
LMArena Math13901267
MATH Level 585%41.6%
Omni-MATH61.6%—
LiveBench Math—42.2%
FrontierMath (Feb 2025 set)4.5%—
FrontierMath Tier 4 (v1)4.2%—

Knowledge Claude Opus 4 leads

Claude Opus 4: 44.0 (#88), Llama-3.3-70B-Instruct: 30.6 (#226)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
GPQA Diamond76.3%47.4%
Confabulations15.9%22.8%
Vectara Hallucination Rate12%4.1%
LMArena Expert13861225
Humanity's Last Exam10.7%—
MMLU-Pro87.5%—
GPQA (HELM)70.8%—
MMLU—86.3%

Multimodal Not comparable

Claude Opus 4: 31.5 (#106), Llama-3.3-70B-Instruct: —

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
LMArena Vision1192—
GeoBench49%—
VPCT38%—

Multilingual Claude Opus 4 leads

Claude Opus 4: 48.8 (#138), Llama-3.3-70B-Instruct: 39.9 (#220)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
LMArena Non-English13621236
LMArena Chinese13861217
LMArena French13721281
LMArena German13911251
LMArena Japanese13311150
LMArena Korean13211143
LMArena Russian13921252
LMArena Spanish13891270

Instruction Following Claude Opus 4 leads

Claude Opus 4: 77.1 (#28), Llama-3.3-70B-Instruct: 71.1 (#157)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
LMArena Instruction Following14061242
LiveBench Instruction Following—82.7%
IFEval91.8%—

Long Context Claude Opus 4 leads

Claude Opus 4: 39.6 (#172), Llama-3.3-70B-Instruct: 26.4 (#295)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
Fiction.LiveBench61.1%33.3%
LMArena Longer Query14221256

Writing & Preference Claude Opus 4 leads

Claude Opus 4: 61.2 (#89), Llama-3.3-70B-Instruct: 47.6 (#207)

BenchmarkClaude Opus 4Llama-3.3-70B-Instruct
LMArena Text13771274
LMArena Creative Writing13871250
LMArena Multi-Turn13961280
Short-Story Creative Writing83.6%—
EQ-Bench Creative Writing1580—
WildBench85.2%—
LiveBench Language—39.2%

Frequently asked questions

Is Claude Opus 4 better than Llama-3.3-70B-Instruct?

Claude Opus 4 is the stronger model overall, scoring 43.1 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 194× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4 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; Claude Opus 4 lists at $15 and $75.

Is Claude Opus 4 or Llama-3.3-70B-Instruct better for coding?

Claude Opus 4 scores higher on coding benchmarks: 47.2 versus 31.0 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4 does, with 200K tokens against 128K.

How many benchmarks do Claude Opus 4 and Llama-3.3-70B-Instruct share?

30 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and Llama-3.3-70B-Instruct has 43.

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