Noometry

Model comparison

Claude Opus 4.7 vs Llama 3.1-70B

Claude Opus 4.7 is the stronger model overall, scoring 58.4 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 4.7's lead doesn't matter for your workload.

Last verified . 24 shared benchmarks.

Claude Opus 4.7 Anthropic

58.4

Rank #17 Confirmed

Llama 3.1-70B Meta

29.4

Rank #299 Confirmed

Summary

  • They share 24 benchmarks with published results for both. Claude Opus 4.7 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 math, where Claude Opus 4.7 leads 66.5 to 12.7.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 97.8% for Claude Opus 4.7 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 4.7.
  • Claude Opus 4.7 accepts more context: 1M tokens versus 128K.
  • Llama 3.1-70B has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.7Llama 3.1-70B
ProviderAnthropicMeta
Noometry Index58.429.4
Released2026-04-142024-07-23
WeightsProprietaryOpen
Context window1M128K
Max output128K4K
Input $ / M tokens$5$0.40
Output $ / M tokens$25$0.40
Results tracked6635

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Category by category

Coding Claude Opus 4.7 leads

Claude Opus 4.7: 59.9 (#10), Llama 3.1-70B: 29.8 (#292)

BenchmarkClaude Opus 4.7Llama 3.1-70B
WeirdML76.4%9%
LMArena Coding15191260
SWE-bench Verified83.5%—
FrontierCode38.5%—
LMArena WebDev1557—
SciCode54.5%—
GSO44.1%—
BigCodeBench Instruct—46.1%
MirrorCode31.1%—
BigCodeBench Complete—54.8%
ALE-Bench1,323—

Agentic & Tool Use Claude Opus 4.7 leads

Claude Opus 4.7: 47.9 (#8), Llama 3.1-70B: 24.9 (#104)

BenchmarkClaude Opus 4.7Llama 3.1-70B
Terminal-Bench80.2%—
APEX-Agents49.2%—
OSWorld 2.018.2%—
TheAgentCompany—6.9%
τ²-bench Banking40.2%—
PostTrainBench28.6%—
BALROG—27.9%
ExploitBench26.5%—
GBAEval43.8%—
GDP.pdf21%—
LMArena Search1233—
Vending-Bench 210,937—

Reasoning Claude Opus 4.7 leads

Claude Opus 4.7: 53.7 (#24), Llama 3.1-70B: 20.8 (#215)

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Hard Prompts15071241
DTBench94.7%60%
LMCA52.2%14.8%
Epoch Capabilities Index156.39125.91
ARC-AGI-275.8%—
SimpleBench61.7%—
Kagi LLM Benchmark80.7%—
NYT Connections (extended)39%—
ARC-AGI-193.5%—
CritPt12%—
Chess Puzzles30%—
Thematic Generalization72.8%—
EBR-Bench19%—
Mystery Game Puzzles28%—
ForecastBench60.3—

Math Claude Opus 4.7 leads

Claude Opus 4.7: 66.5 (#20), Llama 3.1-70B: 12.7 (#298)

BenchmarkClaude Opus 4.7Llama 3.1-70B
OTIS Mock AIME 2024-202597.8%3.6%
LMArena Math14991252
FrontierMath (Tiers 1-3)70.2%—
FrontierMath Tier 431.7%—
MathArena Final-Answer Competitions73.6%—
ProofBench54%—
Omni-MATH—21%
MATH Level 5—36.7%
FrontierMath (Feb 2025 set)43.8%—
FrontierMath Tier 4 (v1)22.9%—

Knowledge Claude Opus 4.7 leads

Claude Opus 4.7: 62.6 (#20), Llama 3.1-70B: 24.1 (#264)

BenchmarkClaude Opus 4.7Llama 3.1-70B
GPQA Diamond90.2%44.2%
LMArena Expert15211209
Humanity's Last Exam36.2%—
SimpleQA Verified51.7%—
MMLU-Pro—65.3%
Vectara Hallucination Rate12%—
GPQA (HELM)—42.6%
MMLU—80.1%

Multimodal Not comparable

Claude Opus 4.7: 41.5 (#29), Llama 3.1-70B: —

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Vision1317—
Blueprint-Bench 224.5%—
Furniture Assembly33.3%—
LMArena Document1495—

Multilingual Claude Opus 4.7 leads

Claude Opus 4.7: 57.5 (#9), Llama 3.1-70B: 38.9 (#220)

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Non-English14811219
LMArena Chinese15301215
LMArena French15051260
LMArena German14941222
LMArena Japanese14721132
LMArena Korean14661140
LMArena Russian14941234
LMArena Spanish14971253

Instruction Following Claude Opus 4.7 leads

Claude Opus 4.7: 78.6 (#9), Llama 3.1-70B: 65.5 (#218)

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Instruction Following14981231
IFEval—82.1%

Long Context Claude Opus 4.7 leads

Claude Opus 4.7: 46.1 (#24), Llama 3.1-70B: 37.6 (#208)

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Longer Query15051241

Writing & Preference Claude Opus 4.7 leads

Claude Opus 4.7: 75.3 (#8), Llama 3.1-70B: 35.6 (#262)

BenchmarkClaude Opus 4.7Llama 3.1-70B
LMArena Text14911261
LMArena Creative Writing14861232
EQ-Bench Creative Writing1914784
LMArena Multi-Turn15061256
WildBench—75.8%
EQ-Bench 41311—

Frequently asked questions

Is Claude Opus 4.7 better than Llama 3.1-70B?

Claude Opus 4.7 is the stronger model overall, scoring 58.4 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 4.7's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.7 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 4.7 lists at $5 and $25.

Is Claude Opus 4.7 or Llama 3.1-70B better for coding?

Claude Opus 4.7 scores higher on coding benchmarks: 59.9 versus 29.8 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.7 does, with 1M tokens against 128K.

How many benchmarks do Claude Opus 4.7 and Llama 3.1-70B share?

24 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Llama 3.1-70B has 35.

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