Noometry

Model comparison

Claude Opus 4.5 vs Llama 3.1-70B

Claude Opus 4.5 is the stronger model overall, scoring 50.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 25× less per token, which makes it the better buy when Claude Opus 4.5's lead doesn't matter for your workload.

Last verified . 25 shared benchmarks.

Claude Opus 4.5 Anthropic

50.5

Rank #39 Confirmed

Llama 3.1-70B Meta

29.4

Rank #299 Confirmed

Summary

  • They share 25 benchmarks with published results for both. Claude Opus 4.5 scores higher in 9 categories and Llama 3.1-70B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Claude Opus 4.5 leads 68.2 to 35.6.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 86.1% for Claude Opus 4.5 and 3.6% for Llama 3.1-70B.
  • Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $5 / $25 for Claude Opus 4.5.
  • Claude Opus 4.5 accepts more context: 200K tokens versus 128K.
  • Llama 3.1-70B has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.5Llama 3.1-70B
ProviderAnthropicMeta
Noometry Index50.529.4
Released2025-11-012024-07-23
WeightsProprietaryOpen
Context window200K128K
Max output64K4K
Input $ / M tokens$5$0.40
Output $ / M tokens$25$0.40
Results tracked6935

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Category by category

Coding Claude Opus 4.5 leads

Claude Opus 4.5: 55.4 (#21), Llama 3.1-70B: 29.8 (#292)

BenchmarkClaude Opus 4.5Llama 3.1-70B
WeirdML63.7%9%
LMArena Coding15041260
SWE-bench Verified76.7%—
SWE-bench Verified (bash only)76.8%—
LMArena WebDev1493—
SWE-bench Multilingual70.7%—
GSO26.5%—
BigCodeBench Instruct—46.1%
BigCodeBench Complete—54.8%
ALE-Bench1,025—
AlgoTune1.77—

Agentic & Tool Use Claude Opus 4.5 leads

Claude Opus 4.5: 47.2 (#11), Llama 3.1-70B: 24.9 (#104)

BenchmarkClaude Opus 4.5Llama 3.1-70B
BALROG43.5%27.9%
Terminal-Bench63.1%—
Berkeley Function Calling Leaderboard77.5%—
GDPval45.5%—
Remote Labor Index3.8%—
TheAgentCompany—6.9%
τ²-bench Airline84%—
τ²-bench Banking24.7%—
τ²-bench Retail79.6%—
τ²-bench Telecom92.3%—
Cybench82%—
DeepResearch Bench54.8%—
OSWorld66.3%—
LMArena Search1180—
METR Time Horizons75%—
Vending-Bench 24,967—

Reasoning Claude Opus 4.5 leads

Claude Opus 4.5: 42.5 (#43), Llama 3.1-70B: 20.8 (#215)

BenchmarkClaude Opus 4.5Llama 3.1-70B
LMArena Hard Prompts14761241
DTBench89.9%60%
LMCA44.5%14.8%
Epoch Capabilities Index150.1125.91
ARC-AGI-237.6%—
SimpleBench62%—
Kagi LLM Benchmark80.2%—
NYT Connections (extended)52.5%—
ARC-AGI-180%—
Chess Puzzles12%—
EnigmaEval11.9%—
EBR-Bench14.3%—
Mystery Game Puzzles22%—
ForecastBench60.7—

Math Claude Opus 4.5 leads

Claude Opus 4.5: 38.5 (#85), Llama 3.1-70B: 12.7 (#298)

BenchmarkClaude Opus 4.5Llama 3.1-70B
OTIS Mock AIME 2024-202586.1%3.6%
LMArena Math14631252
FrontierMath (Tiers 1-3)34.4%—
FrontierMath Tier 44.9%—
ProofBench36%—
Omni-MATH—21%
MATH Level 5—36.7%
FrontierMath (Feb 2025 set)20.7%—
FrontierMath Tier 4 (v1)4.2%—

Knowledge Claude Opus 4.5 leads

Claude Opus 4.5: 56.4 (#38), Llama 3.1-70B: 24.1 (#264)

BenchmarkClaude Opus 4.5Llama 3.1-70B
GPQA Diamond86%44.2%
LMArena Expert14881209
Humanity's Last Exam25.2%—
SimpleQA Verified45.7%—
MMLU-Pro—65.3%
Vectara Hallucination Rate10.9%—
GPQA (HELM)—42.6%
MMLU—80.1%

Multimodal Not comparable

Claude Opus 4.5: 31.1 (#99), Llama 3.1-70B: —

BenchmarkClaude Opus 4.5Llama 3.1-70B
GeoBench75%—
VPCT40%—
Furniture Assembly28.3%—
LMArena Document1462—

Multilingual Claude Opus 4.5 leads

Claude Opus 4.5: 54.5 (#45), Llama 3.1-70B: 38.9 (#220)

BenchmarkClaude Opus 4.5Llama 3.1-70B
LMArena Non-English14381219
LMArena Chinese14701215
LMArena French14711260
LMArena German14491222
LMArena Japanese14151132
LMArena Korean14241140
LMArena Russian14481234
LMArena Spanish14551253

Instruction Following Claude Opus 4.5 leads

Claude Opus 4.5: 77.7 (#20), Llama 3.1-70B: 65.5 (#218)

BenchmarkClaude Opus 4.5Llama 3.1-70B
LMArena Instruction Following14781231
IFEval—82.1%

Long Context Claude Opus 4.5 leads

Claude Opus 4.5: 46.4 (#21), Llama 3.1-70B: 37.6 (#208)

BenchmarkClaude Opus 4.5Llama 3.1-70B
LMArena Longer Query14801241
CL-bench21.1%—

Writing & Preference Claude Opus 4.5 leads

Claude Opus 4.5: 68.2 (#28), Llama 3.1-70B: 35.6 (#262)

BenchmarkClaude Opus 4.5Llama 3.1-70B
LMArena Text14511261
LMArena Creative Writing14451232
EQ-Bench Creative Writing1687784
LMArena Multi-Turn14661256
WildBench—75.8%

Frequently asked questions

Is Claude Opus 4.5 better than Llama 3.1-70B?

Claude Opus 4.5 is the stronger model overall, scoring 50.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 25× less per token, which makes it the better buy when Claude Opus 4.5's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.5 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; Claude Opus 4.5 lists at $5 and $25.

Is Claude Opus 4.5 or Llama 3.1-70B better for coding?

Claude Opus 4.5 scores higher on coding benchmarks: 55.4 versus 29.8 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.5 does, with 200K tokens against 128K.

How many benchmarks do Claude Opus 4.5 and Llama 3.1-70B share?

25 benchmarks have published results for both models. Claude Opus 4.5 has 69 scored results on Noometry and Llama 3.1-70B has 35.

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