Noometry

Model comparison

Claude Opus 4.6 vs Llama 3.2 1B

Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 20.1 on the Noometry Index. Llama 3.2 1B costs 142× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

Last verified . 18 shared benchmarks.

Claude Opus 4.6 Anthropic

58.2

Rank #20 Confirmed

Llama 3.2 1B Meta

20.1

Rank #354 Confirmed

Summary

  • They share 18 benchmarks with published results for both. Claude Opus 4.6 scores higher in 9 categories and Llama 3.2 1B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Claude Opus 4.6 leads 61.9 to 7.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.4% for Claude Opus 4.6 and 0.6% for Llama 3.2 1B.
  • Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $5 / $25 for Claude Opus 4.6.
  • Claude Opus 4.6 accepts more context: 1M tokens versus 60K.
  • Llama 3.2 1B has downloadable open weights; the other is API-only.

Side by side

Claude Opus 4.6Llama 3.2 1B
ProviderAnthropicMeta
Noometry Index58.220.1
Released2026-02-042024-09-24
WeightsProprietaryOpen
Context window1M60K
Max output128K54K
Input $ / M tokens$5$0.027
Output $ / M tokens$25$0.20
Results tracked6822

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Category by category

Coding Claude Opus 4.6 leads

Claude Opus 4.6: 57.2 (#20), Llama 3.2 1B: 21.1 (#338)

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Coding15361070
SWE-bench Verified78.7%—
FrontierCode26.6%—
SWE-bench Verified (bash only)75.6%—
LMArena WebDev1547—
SWE-bench Multilingual72%—
GSO41.2%—
WeirdML78%—
BigCodeBench Instruct—8.2%
BigCodeBench Complete—11.3%
ALE-Bench996.5—
AlgoTune1.47—

Agentic & Tool Use Claude Opus 4.6 leads

Claude Opus 4.6: 51.1 (#4), Llama 3.2 1B: 14.6 (#150)

BenchmarkClaude Opus 4.6Llama 3.2 1B
Terminal-Bench79.8%—
APEX-Agents46.3%—
Berkeley Function Calling Leaderboard—10.8%
Remote Labor Index4.2%—
τ²-bench Banking27.3%—
Cybench93%—
DeepResearch Bench55.3%—
BALROG—6.6%
GBAEval44.1%—
LMArena Search1253—
METR Time Horizons78.9%—
Vending-Bench 28,018—

Reasoning Claude Opus 4.6 leads

Claude Opus 4.6: 57.8 (#23), Llama 3.2 1B: 16.2 (#308)

BenchmarkClaude Opus 4.6Llama 3.2 1B
Chess Puzzles17%0%
LMArena Hard Prompts15271044
Epoch Capabilities Index155.24101.99
ARC-AGI-269.2%—
SimpleBench67.6%—
Kagi LLM Benchmark83.6%—
NYT Connections (extended)92.1%—
ARC-AGI-194%—
EnigmaEval7.6%—
Thematic Generalization80.6%—
EBR-Bench12.7%—
Mystery Game Puzzles25%—
DTBench91.2%—
LMCA55.8%—
ForecastBench60—

Math Claude Opus 4.6 leads

Claude Opus 4.6: 63.0 (#31), Llama 3.2 1B: 10.4 (#313)

BenchmarkClaude Opus 4.6Llama 3.2 1B
OTIS Mock AIME 2024-202594.4%0.6%
LMArena Math15191086
FrontierMath (Tiers 1-3)66%—
FrontierMath Tier 426.8%—
MathArena Final-Answer Competitions78.5%—
ProofBench50%—
FrontierMath (Feb 2025 set)40.7%—
FrontierMath Tier 4 (v1)22.9%—

Knowledge Claude Opus 4.6 leads

Claude Opus 4.6: 61.9 (#26), Llama 3.2 1B: 7.2 (#312)

BenchmarkClaude Opus 4.6Llama 3.2 1B
GPQA Diamond90.5%23.9%
LMArena Expert15461007
Humanity's Last Exam34.4%—
SimpleQA Verified47%—
Vectara Hallucination Rate12.2%—

Multimodal Not comparable

Claude Opus 4.6: 37.3 (#74), Llama 3.2 1B: —

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Vision1316—
Furniture Assembly28.3%—
LMArena Document1507—

Multilingual Claude Opus 4.6 leads

Claude Opus 4.6: 57.9 (#6), Llama 3.2 1B: 23.8 (#292)

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Non-English1489973
LMArena Chinese1551959
LMArena German15021014
LMArena Russian1497941
LMArena French1513—
LMArena Japanese1484—
LMArena Korean1464—
LMArena Spanish1510—

Instruction Following Claude Opus 4.6 leads

Claude Opus 4.6: 79.5 (#4), Llama 3.2 1B: 52.4 (#290)

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Instruction Following15231031

Long Context Claude Opus 4.6 leads

Claude Opus 4.6: 48.1 (#13), Llama 3.2 1B: 31.9 (#274)

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Longer Query15201050
CL-bench20.7%—
CL-bench Life17%—

Writing & Preference Claude Opus 4.6 leads

Claude Opus 4.6: 73.5 (#10), Llama 3.2 1B: 21.3 (#310)

BenchmarkClaude Opus 4.6Llama 3.2 1B
LMArena Text15031055
LMArena Creative Writing15051033
EQ-Bench Creative Writing1809200
LMArena Multi-Turn15131030
EQ-Bench 41223—

Frequently asked questions

Is Claude Opus 4.6 better than Llama 3.2 1B?

Claude Opus 4.6 is the stronger model overall, scoring 58.2 to 20.1 on the Noometry Index. Llama 3.2 1B costs 142× less per token, which makes it the better buy when Claude Opus 4.6's lead doesn't matter for your workload.

Which is cheaper, Claude Opus 4.6 or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Claude Opus 4.6 lists at $5 and $25.

Is Claude Opus 4.6 or Llama 3.2 1B better for coding?

Claude Opus 4.6 scores higher on coding benchmarks: 57.2 versus 21.1 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 4.6 does, with 1M tokens against 60K.

How many benchmarks do Claude Opus 4.6 and Llama 3.2 1B share?

18 benchmarks have published results for both models. Claude Opus 4.6 has 68 scored results on Noometry and Llama 3.2 1B has 22.

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