Model comparison

Laguna M.1 vs Llama-3.3-70B-Instruct

Laguna M.1 is the stronger model overall, scoring 31.9 to 30.3 on the Noometry Index.

Last verified . 0 shared benchmarks.

Laguna M.1 Poolside

31.9

Rank #252 Reported

Llama-3.3-70B-Instruct Meta

30.3

Rank #283 Confirmed

Summary

  • The widest gap is in reasoning, where Laguna M.1 leads 21.9 to 13.7.
  • Laguna M.1 accepts more context: 262K tokens versus 128K.

Side by side

Laguna M.1 and Llama-3.3-70B-Instruct specifications
Laguna M.1Llama-3.3-70B-Instruct
ProviderPoolsideMeta
Noometry Index31.930.3
Released2026-04-282024-12-06
WeightsOpenOpen
Context window262K128K
Max output33K4K
Input $ / M tokens—$0.10
Output $ / M tokens—$0.32
Results tracked343

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Category by category

Coding Laguna M.1 leads

Laguna M.1: 36.4 (#195), Llama-3.3-70B-Instruct: 30.6 (#284)

Coding benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
LMArena WebDev1348—
SciCode—26%
WeirdML—14.4%
BigCodeBench Instruct—46.9%
LiveBench Coding—36.6%
LMArena Coding—1268
BigCodeBench Complete—57.5%

Agentic & Tool Use Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 25.6 (#100)

Agentic & Tool Use benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
Berkeley Function Calling Leaderboard—31.9%
BALROG—23%

Reasoning Laguna M.1 leads

Laguna M.1: 21.9 (#187), Llama-3.3-70B-Instruct: 13.7 (#325)

Reasoning benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
SimpleBench—19.9%
CritPt—0%
LiveBench Reasoning—50.8%
LMArena Hard Prompts—1257
DTBench—59.5%
LiveBench Data Analysis—49.5%
LMCA—17.5%
Surface Evolver Bench15.6%—
Epoch Capabilities Index—127.32
ForecastBench—58.6
LiveBench—50.2%

Math Laguna M.1 leads

Laguna M.1: 20.3 (#276), Llama-3.3-70B-Instruct: 14.3 (#292)

Math benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
OTIS Mock AIME 2024-2025—5.1%
ProofBench0%—
LiveBench Math—42.2%
LMArena Math—1268
MATH Level 5—41.6%

Knowledge Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 30.5 (#220)

Knowledge benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
GPQA Diamond—47.4%
Confabulations—22.8%
Vectara Hallucination Rate—4.1%
LMArena Expert—1225
MMLU—86.3%

Multilingual Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 40.1 (#215)

Multilingual benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
LMArena Non-English—1236
LMArena Chinese—1217
LMArena French—1280
LMArena German—1251
LMArena Japanese—1149
LMArena Korean—1142
LMArena Russian—1252
LMArena Spanish—1269

Instruction Following Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 71.3 (#152)

Instruction Following benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
LiveBench Instruction Following—82.7%
LMArena Instruction Following—1242

Long Context Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 26.4 (#290)

Long Context benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
Fiction.LiveBench—33.3%
LMArena Longer Query—1256

Writing & Preference Not comparable

Laguna M.1: —, Llama-3.3-70B-Instruct: 47.8 (#203)

Writing & Preference benchmarks
BenchmarkLaguna M.1Llama-3.3-70B-Instruct
LMArena Text—1274
LMArena Creative Writing—1250
LMArena Multi-Turn—1279
LiveBench Language—39.2%

Frequently asked questions

Is Laguna M.1 better than Llama-3.3-70B-Instruct?

Laguna M.1 is the stronger model overall, scoring 31.9 to 30.3 on the Noometry Index.

Is Laguna M.1 or Llama-3.3-70B-Instruct better for coding?

Laguna M.1 scores higher on coding benchmarks: 36.4 versus 30.6 in the Noometry coding category.

Which has the bigger context window?

Laguna M.1 does, with 262K tokens against 128K.

How many benchmarks do Laguna M.1 and Llama-3.3-70B-Instruct share?

0 benchmarks have published results for both models. Laguna M.1 has 3 scored results on Noometry and Llama-3.3-70B-Instruct has 43.

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