Noometry

Model comparison

Claude Opus 4.5 vs Llama 3.1-8B

Claude Opus 4.5 is the stronger model overall, scoring 50.5 to 22.8 on the Noometry Index. Llama 3.1-8B costs 174× less per token, which makes it the better buy when Claude Opus 4.5's lead doesn't matter for your workload.

Last verified . 27 shared benchmarks.

Claude Opus 4.5 Anthropic

50.5

Rank #39 Confirmed

Llama 3.1-8B Meta

22.8

Rank #347 Confirmed

Summary

  • They share 27 benchmarks with published results for both. Claude Opus 4.5 scores higher in 9 categories and Llama 3.1-8B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Claude Opus 4.5 leads 56.4 to 8.0.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 86.1% for Claude Opus 4.5 and 1.7% for Llama 3.1-8B.
  • Llama 3.1-8B is cheaper at $0.05 / $0.08 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 3.1-8B has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.5Llama 3.1-8B
ProviderAnthropicMeta
Noometry Index50.522.8
Released2025-11-012024-07-23
WeightsProprietaryOpen
Context window200K128K
Max output64K4K
Input $ / M tokens$5$0.05
Output $ / M tokens$25$0.08
Results tracked6943

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Category by category

Coding Claude Opus 4.5 leads

Claude Opus 4.5: 55.4 (#21), Llama 3.1-8B: 19.9 (#335)

BenchmarkClaude Opus 4.5Llama 3.1-8B
WeirdML63.7%1.7%
LMArena Coding15041195
SWE-bench Verified76.7%—
SWE-bench Verified (bash only)76.8%—
LMArena WebDev1493—
SWE-bench Multilingual70.7%—
SciCode—13.2%
GSO26.5%—
BigCodeBench Instruct—32.8%
BigCodeBench Complete—40.5%
ALE-Bench1,025—
AlgoTune1.77—
HumanEval+—62.8%
MBPP+—55.6%

Agentic & Tool Use Claude Opus 4.5 leads

Claude Opus 4.5: 47.2 (#11), Llama 3.1-8B: 22.3 (#123)

BenchmarkClaude Opus 4.5Llama 3.1-8B
Berkeley Function Calling Leaderboard77.5%25.8%
BALROG43.5%15.1%
Terminal-Bench63.1%—
GDPval45.5%—
Remote Labor Index3.8%—
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 3.1-8B: 14.5 (#316)

BenchmarkClaude Opus 4.5Llama 3.1-8B
Chess Puzzles12%0%
LMArena Hard Prompts14761175
DTBench89.9%50.9%
LMCA44.5%5.4%
Epoch Capabilities Index150.1116.48
ARC-AGI-237.6%—
SimpleBench62%—
Kagi LLM Benchmark80.2%—
NYT Connections (extended)52.5%—
ARC-AGI-180%—
CritPt—0%
EnigmaEval11.9%—
EBR-Bench14.3%—
Mystery Game Puzzles22%—
ForecastBench60.7—
PIQA—81.2%

Math Claude Opus 4.5 leads

Claude Opus 4.5: 38.5 (#85), Llama 3.1-8B: 9.5 (#311)

BenchmarkClaude Opus 4.5Llama 3.1-8B
OTIS Mock AIME 2024-202586.1%1.7%
LMArena Math14631179
FrontierMath (Tiers 1-3)34.4%—
FrontierMath Tier 44.9%—
ProofBench36%—
Omni-MATH—13.7%
MATH Level 5—22.9%
FrontierMath (Feb 2025 set)20.7%—
FrontierMath Tier 4 (v1)4.2%—
GSM8K—82.4%

Knowledge Claude Opus 4.5 leads

Claude Opus 4.5: 56.4 (#38), Llama 3.1-8B: 8.0 (#302)

BenchmarkClaude Opus 4.5Llama 3.1-8B
GPQA Diamond86%27%
LMArena Expert14881144
Humanity's Last Exam25.2%—
SimpleQA Verified45.7%—
MMLU-Pro—40.6%
Vectara Hallucination Rate10.9%—
GPQA (HELM)—24.7%
BoolQ—82.8%
MMLU—56.1%

Multimodal Not comparable

Claude Opus 4.5: 31.1 (#99), Llama 3.1-8B: —

BenchmarkClaude Opus 4.5Llama 3.1-8B
GeoBench75%—
VPCT40%—
Furniture Assembly28.3%—
LMArena Document1462—

Multilingual Claude Opus 4.5 leads

Claude Opus 4.5: 54.5 (#45), Llama 3.1-8B: 34.2 (#244)

BenchmarkClaude Opus 4.5Llama 3.1-8B
LMArena Non-English14381148
LMArena Chinese14701151
LMArena French14711176
LMArena German14491144
LMArena Japanese14151061
LMArena Korean14241053
LMArena Russian14481158
LMArena Spanish14551169

Instruction Following Claude Opus 4.5 leads

Claude Opus 4.5: 77.7 (#20), Llama 3.1-8B: 59.1 (#253)

BenchmarkClaude Opus 4.5Llama 3.1-8B
LMArena Instruction Following14781159
IFEval—74.3%

Long Context Claude Opus 4.5 leads

Claude Opus 4.5: 46.4 (#21), Llama 3.1-8B: 35.8 (#233)

BenchmarkClaude Opus 4.5Llama 3.1-8B
LMArena Longer Query14801182
CL-bench21.1%—

Writing & Preference Claude Opus 4.5 leads

Claude Opus 4.5: 68.2 (#28), Llama 3.1-8B: 29.9 (#285)

BenchmarkClaude Opus 4.5Llama 3.1-8B
LMArena Text14511187
LMArena Creative Writing14451154
EQ-Bench Creative Writing1687713
LMArena Multi-Turn14661172
WildBench—68.7%

Frequently asked questions

Is Claude Opus 4.5 better than Llama 3.1-8B?

Claude Opus 4.5 is the stronger model overall, scoring 50.5 to 22.8 on the Noometry Index. Llama 3.1-8B costs 174× 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 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Claude Opus 4.5 lists at $5 and $25.

Is Claude Opus 4.5 or Llama 3.1-8B better for coding?

Claude Opus 4.5 scores higher on coding benchmarks: 55.4 versus 19.9 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 3.1-8B share?

27 benchmarks have published results for both models. Claude Opus 4.5 has 69 scored results on Noometry and Llama 3.1-8B has 43.

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