Noometry

Model comparison

Claude Opus 4.8 vs Llama 3-8B

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 25.3 on the Noometry Index. Llama 3-8B costs 71× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

Last verified . 23 shared benchmarks.

Claude Opus 4.8 Anthropic

60.7

Rank #9 Confirmed

Llama 3-8B Meta

25.3

Rank #338 Confirmed

Summary

  • They share 23 benchmarks with published results for both. Claude Opus 4.8 scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where Claude Opus 4.8 leads 78.2 to 8.3.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for Claude Opus 4.8 and 1.9% for Llama 3-8B.
  • Llama 3-8B is cheaper at $0.14 / $0.14 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
  • Claude Opus 4.8 accepts more context: 1M tokens versus 8K.
  • Llama 3-8B has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.8Llama 3-8B
ProviderAnthropicMeta
Noometry Index60.725.3
Released2026-05-282024-04-18
WeightsProprietaryOpen
Context window1M8K
Max output128K8K
Input $ / M tokens$5$0.14
Output $ / M tokens$25$0.14
Results tracked6534

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Category by category

Coding Claude Opus 4.8 leads

Claude Opus 4.8: 60.2 (#9), Llama 3-8B: 30.5 (#285)

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Coding14911152
DeepSWE59%—
FrontierCode46.5%—
LMArena WebDev1556—
SciCode53.5%—
GSO47.1%—
WeirdML82.9%—
BigCodeBench Instruct—31.9%
BigCodeBench Complete—36.9%
ALE-Bench1,564—
HumanEval+—56.7%
MBPP+—54.8%

Agentic & Tool Use Not comparable

Claude Opus 4.8: 47.6 (#10), Llama 3-8B: —

BenchmarkClaude Opus 4.8Llama 3-8B
APEX-Agents48.9%—
OSWorld 2.020.6%—
Remote Labor Index8.3%—
τ²-bench Banking39.7%—
DeepResearch Bench50.2%—
PostTrainBench33.8%—
GBAEval70.9%—
GDP.pdf24%—
LMArena Search1204—
Vending-Bench 25,787—

Reasoning Claude Opus 4.8 leads

Claude Opus 4.8: 64.6 (#14), Llama 3-8B: 13.8 (#321)

BenchmarkClaude Opus 4.8Llama 3-8B
Chess Puzzles34%0%
LMArena Hard Prompts14811133
DTBench94.9%43.9%
Epoch Capabilities Index158.3116.33
ForecastBench59.958.6
ARC-AGI-272.1%—
SimpleBench64.8%—
Kagi LLM Benchmark88.8%—
NYT Connections (extended)91.1%—
ARC-AGI-192.5%—
CritPt20.9%—
EnigmaEval23.5%—
EBR-Bench28.6%—
Mystery Game Puzzles36%—
LMCA57.5%—
Surface Evolver Bench87.5%—
Adversarial NLI—57.3%
Bench to the Future 30.14—
WinoGrande—75.7%

Math Claude Opus 4.8 leads

Claude Opus 4.8: 78.2 (#11), Llama 3-8B: 8.3 (#317)

BenchmarkClaude Opus 4.8Llama 3-8B
OTIS Mock AIME 2024-202598.3%1.9%
LMArena Math14871151
FrontierMath (Tiers 1-3)80%—
FrontierMath Tier 456.1%—
MathArena Final-Answer Competitions91.8%—
ProofBench69%—
MATH Level 5—6.1%
FrontierMath (Feb 2025 set)47.2%—
FrontierMath Tier 4 (v1)31.3%—

Knowledge Claude Opus 4.8 leads

Claude Opus 4.8: 61.3 (#26), Llama 3-8B: 7.8 (#303)

BenchmarkClaude Opus 4.8Llama 3-8B
GPQA Diamond91%26.1%
LMArena Expert15011113
SimpleQA Verified53%—
ARC (AI2) Challenge—82.8%
MMLU—68.8%
OpenBookQA—82.6%
TriviaQA—67.7%

Multimodal Not comparable

Claude Opus 4.8: 43.2 (#20), Llama 3-8B: —

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Vision1295—
Blueprint-Bench 214.5%—
Furniture Assembly42.5%—
LMArena Document1475—

Multilingual Claude Opus 4.8 leads

Claude Opus 4.8: 55.4 (#31), Llama 3-8B: 31.0 (#256)

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Non-English14501098
LMArena Chinese15091076
LMArena French14821158
LMArena German14701104
LMArena Japanese1440967
LMArena Korean14321003
LMArena Russian14761109
LMArena Spanish14701172

Instruction Following Claude Opus 4.8 leads

Claude Opus 4.8: 77.6 (#22), Llama 3-8B: 58.7 (#255)

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Instruction Following14761127

Long Context Claude Opus 4.8 leads

Claude Opus 4.8: 45.4 (#37), Llama 3-8B: 34.2 (#246)

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Longer Query14821128

Writing & Preference Claude Opus 4.8 leads

Claude Opus 4.8: 72.1 (#17), Llama 3-8B: 37.7 (#251)

BenchmarkClaude Opus 4.8Llama 3-8B
LMArena Text14601166
LMArena Creative Writing14531150
LMArena Multi-Turn14761152
EQ-Bench Creative Writing1840—
EQ-Bench 41281—

Frequently asked questions

Is Claude Opus 4.8 better than Llama 3-8B?

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 25.3 on the Noometry Index. Llama 3-8B costs 71× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.8 or Llama 3-8B?

Llama 3-8B is cheaper. It lists at $0.14 per million input tokens and $0.14 per million output tokens; Claude Opus 4.8 lists at $5 and $25.

Is Claude Opus 4.8 or Llama 3-8B better for coding?

Claude Opus 4.8 scores higher on coding benchmarks: 60.2 versus 30.5 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.8 does, with 1M tokens against 8K.

How many benchmarks do Claude Opus 4.8 and Llama 3-8B share?

23 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Llama 3-8B has 34.

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