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Claude Sonnet 4.5 vs Llama 3.3 70B Instruct

Claude Sonnet 4.5 leads Llama 3.3 70B Instruct on the Artificial Analysis Intelligence Index, 20.7 to 7.7, and Llama 3.3 70B Instruct costs 20.8x less per output token ($0.72 vs $15.00 per million). Updated October 22, 2026; 39 benchmarks have a result for both.

Claude Sonnet 4.5Anthropic
Coding
39.5
Overall
49.5
Output $/M
$15.00
39
Llama 3.3 70B InstructMeta Llama
Coding
No data
Overall
26.0
Output $/M
$0.72
0
vs boards won of 39 shared

Claude Sonnet 4.5 or Llama 3.3 70B Instruct: which to pick

Only Claude Sonnet 4.5 has a coding score, 39.5 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding.

Pick Llama 3.3 70B Instruct for output tokens 20.8x cheaper ($0.72 vs $15.00 per million).

Shared results
39
Claude Sonnet 4.5 only
56
Llama 3.3 70B Instruct only
13
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 Sonnet 4.5 39.5 from 3 benchmarks, Llama 3.3 70B Instruct not benchmarked.
Widest category
Math, 47.9 points apart on average over 4 shared benchmarks.
Widest single gap
OTIS Mock AIME: Claude Sonnet 4.5 77.8% against Llama 3.3 70B Instruct 5.1%, 72.6 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.5 $15.00 against Llama 3.3 70B Instruct $0.72 per million output tokens, 20.8x apart.
Context window
Claude Sonnet 4.5 takes 1M tokens, Llama 3.3 70B Instruct 131K.

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 Sonnet 4.5BarsLlama 3.3 70B InstructTies
Coding40
Intelligence20
Agentic work10
Reasoning50
Math40
Knowledge40
General190
All shared boards390
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
SWE-bench Verified74.8%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Multilingual67.0%Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev1394Not measuredOnly Claude Sonnet 4.5 measured
AA Coding Index52.111.9Claude Sonnet 4.5
LiveCodeBench (Vals AI)73.0%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Verified (Vals AI)70.0%Not measuredOnly Claude Sonnet 4.5 measured
Vibe Code Bench (Vals AI)22.6%Not measuredOnly Claude Sonnet 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured28.8%Only Llama 3.3 70B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Llama 3.3 70B Instruct measured
Terminal-Bench46.5%Not measuredOnly Claude Sonnet 4.5 measured
GSO-Bench14.7%Not measuredOnly Claude Sonnet 4.5 measured
WeirdML47.7%14.4%Claude Sonnet 4.5
Cybench60.0%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: coding14881268Claude Sonnet 4.5
LMArena Text: software and IT14731273Claude Sonnet 4.5
LMArena WebDev: React1386Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev: HTML1399Not measuredOnly Claude Sonnet 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 index20
Intelligence benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
AA Intelligence Index20.77.7Claude Sonnet 4.5
Epoch Capabilities Index146.7127.3Claude Sonnet 4.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
AA Agentic Index15.8Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building web apps1060Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building full-stack apps1050Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building mobile apps1137Not measuredOnly Claude Sonnet 4.5 measured
τ²-Bench TelecomNot measured26.6%Only Llama 3.3 70B Instruct measured
METR time horizons67.4%Not measuredOnly Claude Sonnet 4.5 measured
Remote Labor Index2.1%Not measuredOnly Claude Sonnet 4.5 measured
GDPval42.5%Not measuredOnly Claude Sonnet 4.5 measured
BALROGNot measured23.0%Only Llama 3.3 70B Instruct measured
DeepResearch Bench52.6%Not measuredOnly Claude Sonnet 4.5 measured
OSWorld62.9%Not measuredOnly Claude Sonnet 4.5 measured
Vending-Bench 2$3,839Not measuredOnly Claude Sonnet 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)73.2%31.9%Claude Sonnet 4.5
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
GPQA Diamond81.6%Not measuredOnly Claude Sonnet 4.5 measured
MMMU Pro (Vals AI)79.3%Not measuredOnly Claude Sonnet 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured49.8%Only Llama 3.3 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured3.6%Only Llama 3.3 70B Instruct measured
GPQA Diamond (Epoch AI run)82.3%47.4%Claude Sonnet 4.5
ARC-AGI63.7%Not measuredOnly Claude Sonnet 4.5 measured
ARC-AGI-213.6%Not measuredOnly Claude Sonnet 4.5 measured
SimpleBench54.3%19.9%Claude Sonnet 4.5
Chess puzzles10.0%Not measuredOnly Claude Sonnet 4.5 measured
Mystery game puzzles17.0%Not measuredOnly Claude Sonnet 4.5 measured
EBR-bench2.4%Not measuredOnly Claude Sonnet 4.5 measured
VPCT39.8%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: hard prompts14621257Claude Sonnet 4.5
LMArena Text: expert14831225Claude Sonnet 4.5
LMArena Text: hard prompts in English14711277Claude Sonnet 4.5
Kagi LLM Benchmark57.9%Not measuredOnly Claude Sonnet 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 index40
Math benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
AIME88.2%Not measuredOnly Claude Sonnet 4.5 measured
MGSM (Vals AI)94.3%Not measuredOnly Claude Sonnet 4.5 measured
AA Math IndexNot measured7.7Only Llama 3.3 70B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured7.7%Only Llama 3.3 70B Instruct measured
OTIS Mock AIME77.8%5.1%Claude Sonnet 4.5
FrontierMath, tiers 1 to 323.9%Not measuredOnly Claude Sonnet 4.5 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Sonnet 4.5 measured
ProofBench19.0%Not measuredOnly Claude Sonnet 4.5 measured
MATH level 597.7%41.6%Claude Sonnet 4.5
LMArena Text: math14491267Claude Sonnet 4.5
LMArena Text: mathematical work14621267Claude Sonnet 4.5
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
MMLU Pro87.4%Not measuredOnly Claude Sonnet 4.5 measured
LegalBench (Vals AI)84.1%Not measuredOnly Claude Sonnet 4.5 measured
CaseLaw (Vals AI)62.2%Not measuredOnly Claude Sonnet 4.5 measured
CorpFin (Vals AI)62.0%Not measuredOnly Claude Sonnet 4.5 measured
TaxEval (Vals AI)73.3%Not measuredOnly Claude Sonnet 4.5 measured
MortgageTax (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.5 measured
MedQA (Vals AI)94.7%Not measuredOnly Claude Sonnet 4.5 measured
MedCode (Vals AI)44.1%Not measuredOnly Claude Sonnet 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured71.3%Only Llama 3.3 70B Instruct measured
SimpleQA Verified30.7%Not measuredOnly Claude Sonnet 4.5 measured
MMLUNot measured86.3%Only Llama 3.3 70B Instruct measured
LMArena Text: science14481284Claude Sonnet 4.5
LMArena Text: medicine and healthcare14441275Claude Sonnet 4.5
LMArena Text: legal and government14511284Claude Sonnet 4.5
LMArena Text: business and finance14401243Claude Sonnet 4.5
FACTS Benchmark Suite40.6%Not measuredOnly Claude Sonnet 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 Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
Design Arena: websites1189Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: UI components1170Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: game dev1166Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: data viz1167Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: 3D1157Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: all code categories1182Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: SVG1115Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: ASCII art1205Not measuredOnly Claude Sonnet 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 index190
General benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B InstructLeader
SAGE (Vals AI)36.1%Not measuredOnly Claude Sonnet 4.5 measured
MedScribe (Vals AI)84.5%Not measuredOnly Claude Sonnet 4.5 measured
IFBenchNot measured47.1%Only Llama 3.3 70B Instruct measured
Long context reasoning (AA-LCR)Not measured15.7%Only Llama 3.3 70B Instruct measured
DTBench83.2%59.5%Claude Sonnet 4.5
LMCA38.8%17.5%Claude Sonnet 4.5
Fiction.LiveBenchNot measured33.3%Only Llama 3.3 70B Instruct measured
LMArena Text14381274Claude Sonnet 4.5
LMArena Text: instruction following14591242Claude Sonnet 4.5
LMArena Text: creative writing14421250Claude Sonnet 4.5
LMArena Text: English14501303Claude Sonnet 4.5
LMArena Text: non-English14251236Claude Sonnet 4.5
LMArena Text: Chinese14601217Claude Sonnet 4.5
LMArena Text: German14271251Claude Sonnet 4.5
LMArena Text: Japanese13901150Claude Sonnet 4.5
LMArena Text: Korean14021142Claude Sonnet 4.5
LMArena Text: French14591282Claude Sonnet 4.5
LMArena Text: Spanish14581269Claude Sonnet 4.5
LMArena Text: Russian14371252Claude Sonnet 4.5
LMArena Text: Polish14231259Claude Sonnet 4.5
LMArena Text: multi-turn14651280Claude Sonnet 4.5
LMArena Text: longer queries14751255Claude Sonnet 4.5
LMArena Text: writing and language14421255Claude Sonnet 4.5
LMArena Text: entertainment and media14281241Claude Sonnet 4.5
LMArena Document1450Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Sonnet 4.5 and Llama 3.3 70B Instruct
BenchmarkClaude Sonnet 4.5Llama 3.3 70B 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 Sonnet 4.5$0.011Fits in one request
Llama 3.3 70B Instruct$0.0008Fits in one request

Llama 3.3 70B Instruct costs less

Repository review

50K input + 3K output tokens

Claude Sonnet 4.5$0.195Fits in one request
Llama 3.3 70B Instruct$0.025Fits in one request

Llama 3.3 70B Instruct costs less

Agent loop

200K input + 10K output tokens

Claude Sonnet 4.5$0.750Fits in one request
Llama 3.3 70B Instruct$0.097Exceeds the context window

Llama 3.3 70B 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 Sonnet 4.5 and Llama 3.3 70B Instruct
SpecificationAnthropic Claude Sonnet 4.5Meta Llama 3.3 70B Instruct
MakerAnthropicMeta Llama
WeightsNo public weights listedOpen weights
ReleasedSeptember 29, 2025December 6, 2024
Context window1M131K
Input $/Mtok$3.00$0.45
Output $/Mtok$15.00$0.72
Coding index39.5Not benchmarked
Independent measurements behind it30
Cost per solved task$1.16Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.5 better than Llama 3.3 70B Instruct for coding?

Only Claude Sonnet 4.5 has a coding score, 39.5 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.3 70B Instruct for output tokens 20.8x cheaper ($0.72 vs $15.00 per million).

Which is cheaper, Claude Sonnet 4.5 or Llama 3.3 70B Instruct?

Claude Sonnet 4.5 costs $3.00 per million input tokens and $15.00 per million output tokens; Llama 3.3 70B Instruct costs $0.45 and $0.72. Cost per solved task is known for Claude Sonnet 4.5 only.

Which has the bigger context window, Claude Sonnet 4.5 or Llama 3.3 70B Instruct?

Claude Sonnet 4.5, with 1M tokens against 131K.

How many benchmarks is the Claude Sonnet 4.5 vs Llama 3.3 70B Instruct comparison based on?

39 benchmarks have a result for both models as of October 22, 2026. Claude Sonnet 4.5's coding index rests on 3 independent benchmarks and Llama 3.3 70B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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