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Claude Opus 4.5 vs Llama 3.2 1B Instruct

Claude Opus 4.5 leads Llama 3.2 1B Instruct on the Artificial Analysis Intelligence Index, 29.1 to 4.8, and Llama 3.2 1B Instruct costs 124.4x less per output token ($0.201 vs $25.00 per million). Updated October 21, 2026; 38 benchmarks have a result for both.

Claude Opus 4.5Anthropic
Coding
44.0
Overall
55.7
Output $/M
$25.00
38
Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
9.6
Output $/M
$0.201
0
vs boards won of 38 shared

Claude Opus 4.5 or Llama 3.2 1B Instruct: which to pick

Only Claude Opus 4.5 has a coding score, 44.0 on the Vibe Coding Index; Llama 3.2 1B Instruct has none, so the two cannot be ranked on coding.

Pick Llama 3.2 1B Instruct for output tokens 124.4x cheaper ($0.201 vs $25.00 per million).

Shared results
38
Claude Opus 4.5 only
70
Llama 3.2 1B Instruct only
0
Like-for-like categories
7 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Claude Opus 4.5 44.0 from 3 benchmarks, Llama 3.2 1B Instruct not benchmarked.
Widest category
Math, 78.5 points apart on average over 5 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): Claude Opus 4.5 91.3% against Llama 3.2 1B Instruct 0.0%, 91.3 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.5 $25.00 against Llama 3.2 1B Instruct $0.201 per million output tokens, 124.4x apart.
Context window
Claude Opus 4.5 takes 200K tokens, Llama 3.2 1B Instruct 60K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryClaude Opus 4.5BarsLlama 3.2 1B InstructTies
Coding40
Intelligence10
Agentic work30
Reasoning60
Math50
Knowledge50
General140
All shared boards380
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
SWE-bench Verified79.2%Not measuredOnly Claude Opus 4.5 measured
SWE-bench (full test set)52.6%Not measuredOnly Claude Opus 4.5 measured
SWE-bench Multilingual70.7%Not measuredOnly Claude Opus 4.5 measured
LMArena WebDev1494Not measuredOnly Claude Opus 4.5 measured
LiveCodeBench (Vals AI)83.7%Not measuredOnly Claude Opus 4.5 measured
SWE-bench Verified (Vals AI)76.4%Not measuredOnly Claude Opus 4.5 measured
Vibe Code Bench (Vals AI)20.6%Not measuredOnly Claude Opus 4.5 measured
LiveCodeBench (Artificial Analysis run)87.1%1.9%Claude Opus 4.5
Terminal-Bench Hard (Artificial Analysis run)47.0%0.0%Claude Opus 4.5
Terminal-Bench63.1%Not measuredOnly Claude Opus 4.5 measured
GSO-Bench26.5%Not measuredOnly Claude Opus 4.5 measured
WeirdML63.7%Not measuredOnly Claude Opus 4.5 measured
Cybench82.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: coding15031070Claude Opus 4.5
LMArena Text: software and IT14831056Claude Opus 4.5
LMArena WebDev: React1478Not measuredOnly Claude Opus 4.5 measured
LMArena WebDev: HTML1510Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
AA Intelligence Index29.14.8Claude Opus 4.5
Epoch Capabilities Index150.1Not measuredOnly Claude Opus 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index30
Agentic work benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
Design Arena: agents building web apps1159Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building full-stack apps1156Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building mobile apps1189Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building Android apps1175Not measuredOnly Claude Opus 4.5 measured
τ²-Bench Telecom89.5%0.0%Claude Opus 4.5
METR time horizons75.0%Not measuredOnly Claude Opus 4.5 measured
Remote Labor Index3.8%Not measuredOnly Claude Opus 4.5 measured
GDPval45.5%Not measuredOnly Claude Opus 4.5 measured
BALROG43.5%6.6%Claude Opus 4.5
DeepResearch Bench54.8%Not measuredOnly Claude Opus 4.5 measured
OSWorld66.3%Not measuredOnly Claude Opus 4.5 measured
Vending-Bench 2$4,967Not measuredOnly Claude Opus 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)77.5%10.8%Claude Opus 4.5
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
GPQA Diamond85.9%Not measuredOnly Claude Opus 4.5 measured
MMMU Pro (Vals AI)83.0%Not measuredOnly Claude Opus 4.5 measured
GPQA Diamond (Artificial Analysis run)86.6%19.6%Claude Opus 4.5
Humanity's Last Exam (Artificial Analysis run)30.1%5.5%Claude Opus 4.5
GPQA Diamond (Epoch AI run)86.0%23.9%Claude Opus 4.5
ARC-AGI80.0%Not measuredOnly Claude Opus 4.5 measured
ARC-AGI-237.6%Not measuredOnly Claude Opus 4.5 measured
SimpleBench62.0%Not measuredOnly Claude Opus 4.5 measured
Chess puzzles14.0%Not measuredOnly Claude Opus 4.5 measured
Mystery game puzzles22.0%Not measuredOnly Claude Opus 4.5 measured
EBR-bench14.3%Not measuredOnly Claude Opus 4.5 measured
VPCT40.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: hard prompts14761044Claude Opus 4.5
LMArena Text: expert14871007Claude Opus 4.5
LMArena Text: hard prompts in English14821087Claude Opus 4.5
Kagi LLM Benchmark80.2%Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index50
Math benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
AIME95.4%Not measuredOnly Claude Opus 4.5 measured
MGSM (Vals AI)95.2%Not measuredOnly Claude Opus 4.5 measured
AA Math Index91.30.0Claude Opus 4.5
AIME 2025 (Artificial Analysis run)91.3%0.0%Claude Opus 4.5
OTIS Mock AIME86.1%0.6%Claude Opus 4.5
FrontierMath, tiers 1 to 334.4%Not measuredOnly Claude Opus 4.5 measured
FrontierMath, tier 44.9%Not measuredOnly Claude Opus 4.5 measured
ProofBench36.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: math14631086Claude Opus 4.5
LMArena Text: mathematical work14681098Claude Opus 4.5
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
MMLU Pro87.3%Not measuredOnly Claude Opus 4.5 measured
LegalBench (Vals AI)84.6%Not measuredOnly Claude Opus 4.5 measured
CaseLaw (Vals AI)62.6%Not measuredOnly Claude Opus 4.5 measured
CorpFin (Vals AI)65.1%Not measuredOnly Claude Opus 4.5 measured
TaxEval (Vals AI)74.9%Not measuredOnly Claude Opus 4.5 measured
MortgageTax (Vals AI)68.7%Not measuredOnly Claude Opus 4.5 measured
MedQA (Vals AI)95.9%Not measuredOnly Claude Opus 4.5 measured
MedCode (Vals AI)49.2%Not measuredOnly Claude Opus 4.5 measured
MMLU Pro (Artificial Analysis run)89.5%20.0%Claude Opus 4.5
SimpleQA Verified45.7%Not measuredOnly Claude Opus 4.5 measured
GeoBench75.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: science14541055Claude Opus 4.5
LMArena Text: medicine and healthcare14441009Claude Opus 4.5
LMArena Text: legal and government14591071Claude Opus 4.5
LMArena Text: business and finance14481000Claude Opus 4.5
FACTS Benchmark Suite43.9%Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
Design Arena: websites1247Not measuredOnly Claude Opus 4.5 measured
Design Arena: UI components1238Not measuredOnly Claude Opus 4.5 measured
Design Arena: game dev1229Not measuredOnly Claude Opus 4.5 measured
Design Arena: data viz1243Not measuredOnly Claude Opus 4.5 measured
Design Arena: 3D1214Not measuredOnly Claude Opus 4.5 measured
Design Arena: all code categories1242Not measuredOnly Claude Opus 4.5 measured
Design Arena: SVG1181Not measuredOnly Claude Opus 4.5 measured
Design Arena: ASCII art1190Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index140
General benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
SAGE (Vals AI)52.1%Not measuredOnly Claude Opus 4.5 measured
MedScribe (Vals AI)85.3%Not measuredOnly Claude Opus 4.5 measured
IFBench58.0%22.8%Claude Opus 4.5
Long context reasoning (AA-LCR)77.3%6.7%Claude Opus 4.5
DTBench89.9%Not measuredOnly Claude Opus 4.5 measured
LMCA44.5%Not measuredOnly Claude Opus 4.5 measured
CL-bench21.1%Not measuredOnly Claude Opus 4.5 measured
Furniture assembly28.3%Not measuredOnly Claude Opus 4.5 measured
LMArena Text14511055Claude Opus 4.5
LMArena Text: instruction following14781031Claude Opus 4.5
LMArena Text: creative writing14451033Claude Opus 4.5
LMArena Text: English14611117Claude Opus 4.5
LMArena Text: non-English1438973Claude Opus 4.5
LMArena Text: Chinese1470959Claude Opus 4.5
LMArena Text: German14491014Claude Opus 4.5
LMArena Text: Japanese1417Not measuredOnly Claude Opus 4.5 measured
LMArena Text: Korean1424Not measuredOnly Claude Opus 4.5 measured
LMArena Text: French1471Not measuredOnly Claude Opus 4.5 measured
LMArena Text: Spanish1457Not measuredOnly Claude Opus 4.5 measured
LMArena Text: Russian1447941Claude Opus 4.5
LMArena Text: Polish1439Not measuredOnly Claude Opus 4.5 measured
LMArena Text: multi-turn14661030Claude Opus 4.5
LMArena Text: longer queries14791050Claude Opus 4.5
LMArena Text: writing and language14521030Claude Opus 4.5
LMArena Text: entertainment and media14341025Claude Opus 4.5
LMArena Document1462Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.5 and Llama 3.2 1B Instruct
BenchmarkClaude Opus 4.5Llama 3.2 1B InstructLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Claude Opus 4.5$0.018Fits in one request
Llama 3.2 1B Instruct$0.0001Fits in one request

Llama 3.2 1B Instruct costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.5$0.325Fits in one request
Llama 3.2 1B Instruct$0.0020Fits in one request

Llama 3.2 1B Instruct costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.5$1.25Exceeds the context window
Llama 3.2 1B Instruct$0.0074Exceeds the context window

Llama 3.2 1B Instruct costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Claude Opus 4.5 and Llama 3.2 1B Instruct
SpecificationAnthropic Claude Opus 4.5Meta Llama 3.2 1B Instruct
MakerAnthropicMeta Llama
WeightsNo public weights listedOpen weights
ReleasedNovember 24, 2025September 25, 2024
Context window200K60K
Input $/Mtok$5.00$0.027
Output $/Mtok$25.00$0.201
Coding index44.0Not benchmarked
Independent measurements behind it30
Cost per solved task$1.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.5 better than Llama 3.2 1B Instruct for coding?

Only Claude Opus 4.5 has a coding score, 44.0 on the Vibe Coding Index; Llama 3.2 1B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.2 1B Instruct for output tokens 124.4x cheaper ($0.201 vs $25.00 per million).

Which is cheaper, Claude Opus 4.5 or Llama 3.2 1B Instruct?

Claude Opus 4.5 costs $5.00 per million input tokens and $25.00 per million output tokens; Llama 3.2 1B Instruct costs $0.027 and $0.201. Cost per solved task is known for Claude Opus 4.5 only.

Which has the bigger context window, Claude Opus 4.5 or Llama 3.2 1B Instruct?

Claude Opus 4.5, with 200K tokens against 60K.

How many benchmarks is the Claude Opus 4.5 vs Llama 3.2 1B Instruct comparison based on?

38 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.5's coding index rests on 3 independent benchmarks and Llama 3.2 1B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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