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Claude Haiku 4.5 vs Llama 3.1 70B Instruct

Claude Haiku 4.5 leads Llama 3.1 70B Instruct on the Artificial Analysis Intelligence Index, 16.9 to 6.6, and Llama 3.1 70B Instruct costs 8.9x less per output token ($0.56 vs $5.00 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

Claude Haiku 4.5Anthropic
Coding
35.6
Overall
41.0
Output $/M
$5.00
36
Llama 3.1 70B InstructMeta Llama
Coding
No data
Overall
24.3
Output $/M
$0.56
0
vs boards won of 36 shared

Claude Haiku 4.5 or Llama 3.1 70B Instruct: which to pick

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Llama 3.1 70B Instruct has none, so the two cannot be ranked on coding.

Pick Llama 3.1 70B Instruct for output tokens 8.9x cheaper ($0.56 vs $5.00 per million).

Shared results
36
Claude Haiku 4.5 only
59
Llama 3.1 70B Instruct only
11
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 Haiku 4.5 35.6 from 4 benchmarks, Llama 3.1 70B Instruct not benchmarked.
Widest category
Math, 44.1 points apart on average over 4 shared benchmarks.
Widest single gap
OTIS Mock AIME: Claude Haiku 4.5 66.7% against Llama 3.1 70B Instruct 3.6%, 63.1 points apart on a 0 to 100 scale.
Output price
Claude Haiku 4.5 $5.00 against Llama 3.1 70B Instruct $0.56 per million output tokens, 8.9x apart.
Context window
Claude Haiku 4.5 takes 200K tokens, Llama 3.1 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 Haiku 4.5BarsLlama 3.1 70B InstructTies
Coding30
Intelligence20
Agentic work10
Reasoning40
Math40
Knowledge40
General180
All shared boards360
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
SWE-bench Verified66.6%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Multilingual64.7%Not measuredOnly Claude Haiku 4.5 measured
LiveBench coding48.1%Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev1330Not measuredOnly Claude Haiku 4.5 measured
AA Coding Index43.9Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Vals AI)41.2%Not measuredOnly Claude Haiku 4.5 measured
SWE-bench Verified (Vals AI)66.6%Not measuredOnly Claude Haiku 4.5 measured
Vibe Code Bench (Vals AI)11.4%Not measuredOnly Claude Haiku 4.5 measured
Code migration (Vals AI)7.5%Not measuredOnly Claude Haiku 4.5 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Haiku 4.5 measured
Terminal-Bench 2.1 (Vals AI)43.8%Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured23.2%Only Llama 3.1 70B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.0%Only Llama 3.1 70B Instruct measured
Terminal-Bench35.5%Not measuredOnly Claude Haiku 4.5 measured
WeirdML45.4%9.0%Claude Haiku 4.5
LMArena Text: coding14541260Claude Haiku 4.5
LMArena Text: software and IT14391260Claude Haiku 4.5
LMArena WebDev: React1326Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev: HTML1318Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
AA Intelligence Index16.96.6Claude Haiku 4.5
Epoch Capabilities Index142.2125.9Claude Haiku 4.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
AA Agentic Index8.0Not measuredOnly Claude Haiku 4.5 measured
LiveBench research42.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench browser40.0%Not measuredOnly Claude Haiku 4.5 measured
LiveBench long agentic11.1%Not measuredOnly Claude Haiku 4.5 measured
Finance Agent (Vals AI)31.0%Not measuredOnly Claude Haiku 4.5 measured
Tax Agent Bench (Vals AI)5.9%Not measuredOnly Claude Haiku 4.5 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly Claude Haiku 4.5 measured
Excel Modeling Benchmark (Vals AI)22.7%Not measuredOnly Claude Haiku 4.5 measured
τ²-Bench TelecomNot measured15.2%Only Llama 3.1 70B Instruct measured
BALROG31.2%27.9%Claude Haiku 4.5
DeepResearch Bench45.5%Not measuredOnly Claude Haiku 4.5 measured
TheAgentCompanyNot measured6.9%Only Llama 3.1 70B Instruct measured
Vending-Bench 2$459Not measuredOnly Claude Haiku 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)68.7%Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
GPQA Diamond72.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench reasoning61.7%Not measuredOnly Claude Haiku 4.5 measured
MMMU Pro (Vals AI)46.1%Not measuredOnly Claude Haiku 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured40.9%Only Llama 3.1 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.5%Only Llama 3.1 70B Instruct measured
GPQA Diamond (Epoch AI run)71.2%44.2%Claude Haiku 4.5
ARC-AGI47.7%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI-24.0%Not measuredOnly Claude Haiku 4.5 measured
Chess puzzles8.0%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: hard prompts14211241Claude Haiku 4.5
LMArena Text: expert14431209Claude Haiku 4.5
LMArena Text: hard prompts in English14351261Claude Haiku 4.5
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
AIME82.7%Not measuredOnly Claude Haiku 4.5 measured
MGSM (Vals AI)92.2%Not measuredOnly Claude Haiku 4.5 measured
AA Math IndexNot measured4.0Only Llama 3.1 70B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured4.0%Only Llama 3.1 70B Instruct measured
OTIS Mock AIME66.7%3.6%Claude Haiku 4.5
MATH level 596.4%36.7%Claude Haiku 4.5
LMArena Text: math13981252Claude Haiku 4.5
LMArena Text: mathematical work14301253Claude Haiku 4.5
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
MMLU Pro78.7%Not measuredOnly Claude Haiku 4.5 measured
LegalBench (Vals AI)81.2%Not measuredOnly Claude Haiku 4.5 measured
CaseLaw (Vals AI)56.5%Not measuredOnly Claude Haiku 4.5 measured
CorpFin (Vals AI)60.6%Not measuredOnly Claude Haiku 4.5 measured
TaxEval (Vals AI)67.5%Not measuredOnly Claude Haiku 4.5 measured
MortgageTax (Vals AI)62.2%Not measuredOnly Claude Haiku 4.5 measured
MedQA (Vals AI)79.6%Not measuredOnly Claude Haiku 4.5 measured
MedCode (Vals AI)32.7%Not measuredOnly Claude Haiku 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured67.6%Only Llama 3.1 70B Instruct measured
SimpleQA Verified13.2%Not measuredOnly Claude Haiku 4.5 measured
MMLUNot measured80.1%Only Llama 3.1 70B Instruct measured
LMArena Text: science14061276Claude Haiku 4.5
LMArena Text: medicine and healthcare13941257Claude Haiku 4.5
LMArena Text: legal and government14001283Claude Haiku 4.5
LMArena Text: business and finance14001235Claude Haiku 4.5
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
Design Arena: websites1122Not measuredOnly Claude Haiku 4.5 measured
Design Arena: UI components1097Not measuredOnly Claude Haiku 4.5 measured
Design Arena: game dev1097Not measuredOnly Claude Haiku 4.5 measured
Design Arena: data viz1124Not measuredOnly Claude Haiku 4.5 measured
Design Arena: 3D1071Not measuredOnly Claude Haiku 4.5 measured
Design Arena: all code categories1114Not measuredOnly Claude Haiku 4.5 measured
Design Arena: SVG1025Not measuredOnly Claude Haiku 4.5 measured
Design Arena: ASCII art1140Not measuredOnly Claude Haiku 4.5 measured
LiveBench design59.9%Not measuredOnly Claude Haiku 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 70B InstructLeader
LiveBench data analysis59.3%Not measuredOnly Claude Haiku 4.5 measured
Public Benefits Bench (Vals AI)54.3%Not measuredOnly Claude Haiku 4.5 measured
SAGE (Vals AI)31.8%Not measuredOnly Claude Haiku 4.5 measured
MedScribe (Vals AI)85.2%Not measuredOnly Claude Haiku 4.5 measured
Vals Multimodal Index42.9%Not measuredOnly Claude Haiku 4.5 measured
IFBenchNot measured34.4%Only Llama 3.1 70B Instruct measured
DTBench73.6%60.0%Claude Haiku 4.5
LMCA30.9%14.8%Claude Haiku 4.5
ExploitBench13.7%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text13971261Claude Haiku 4.5
LMArena Text: instruction following14141231Claude Haiku 4.5
LMArena Text: creative writing13711232Claude Haiku 4.5
LMArena Text: English14141294Claude Haiku 4.5
LMArena Text: non-English13771219Claude Haiku 4.5
LMArena Text: Chinese14181215Claude Haiku 4.5
LMArena Text: German13741222Claude Haiku 4.5
LMArena Text: Japanese13381132Claude Haiku 4.5
LMArena Text: Korean13461140Claude Haiku 4.5
LMArena Text: French14111262Claude Haiku 4.5
LMArena Text: Spanish14211253Claude Haiku 4.5
LMArena Text: Russian13811234Claude Haiku 4.5
LMArena Text: Polish1343Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: multi-turn14091256Claude Haiku 4.5
LMArena Text: longer queries14271241Claude Haiku 4.5
LMArena Text: writing and language13861236Claude Haiku 4.5
LMArena Text: entertainment and media13691230Claude Haiku 4.5
LMArena Document1420Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Haiku 4.5 and Llama 3.1 70B Instruct
BenchmarkClaude Haiku 4.5Llama 3.1 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 Haiku 4.5$0.0035Fits in one request
Llama 3.1 70B Instruct$0.0008Fits in one request

Llama 3.1 70B Instruct costs less

Repository review

50K input + 3K output tokens

Claude Haiku 4.5$0.065Fits in one request
Llama 3.1 70B Instruct$0.030Fits in one request

Llama 3.1 70B Instruct costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 4.5$0.250Exceeds the context window
Llama 3.1 70B Instruct$0.118Exceeds the context window

Llama 3.1 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 Haiku 4.5 and Llama 3.1 70B Instruct
SpecificationAnthropic Claude Haiku 4.5Meta Llama 3.1 70B Instruct
MakerAnthropicMeta Llama
WeightsNo public weights listedOpen weights
ReleasedOctober 15, 2025July 23, 2024
Context window200K131K
Input $/Mtok$1.00$0.56
Output $/Mtok$5.00$0.56
Coding index35.6Not benchmarked
Independent measurements behind it40
Cost per solved task$0.56Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Haiku 4.5 better than Llama 3.1 70B Instruct for coding?

Only Claude Haiku 4.5 has a coding score, 35.6 on the Vibe Coding Index; Llama 3.1 70B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.1 70B Instruct for output tokens 8.9x cheaper ($0.56 vs $5.00 per million).

Which is cheaper, Claude Haiku 4.5 or Llama 3.1 70B Instruct?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; Llama 3.1 70B Instruct costs $0.56 and $0.56. Cost per solved task is known for Claude Haiku 4.5 only.

Which has the bigger context window, Claude Haiku 4.5 or Llama 3.1 70B Instruct?

Claude Haiku 4.5, with 200K tokens against 131K.

How many benchmarks is the Claude Haiku 4.5 vs Llama 3.1 70B Instruct comparison based on?

36 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 4.5's coding index rests on 4 independent benchmarks and Llama 3.1 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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