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GPT-4.1 Nano vs Llama 3.3 70B Instruct

GPT-4.1 Nano leads Llama 3.3 70B Instruct on the Artificial Analysis Intelligence Index, 7.8 to 7.7, and GPT-4.1 Nano costs 1.8x less per output token ($0.40 vs $0.72 per million). Updated October 22, 2026; 45 benchmarks have a result for both.

Replace GPT-4.1 Nano Replace Llama 3.3 70B Instruct
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
36
Llama 3.3 70B InstructMeta Llama
Coding
No data
Overall
26.0
Output $/M
$0.72
9
vs boards won of 45 shared

GPT-4.1 Nano or Llama 3.3 70B Instruct: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-4.1 Nano for output tokens 1.8x cheaper ($0.40 vs $0.72 per million) and a larger context window (1.05M against 131K tokens).

Model AGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BLlama 3.3 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
45
GPT-4.1 Nano only
26
Llama 3.3 70B Instruct only
7
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
GPT-4.1 Nano not benchmarked, Llama 3.3 70B Instruct not benchmarked.
Widest category
Math, 14.5 points apart on average over 6 shared benchmarks.
Widest single gap
MATH level 5: GPT-4.1 Nano 70.0% against Llama 3.3 70B Instruct 41.6%, 28.4 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Llama 3.3 70B Instruct $0.72 per million output tokens, 1.8x apart.
Context window
GPT-4.1 Nano takes 1.05M 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
CategoryGPT-4.1 NanoBarsLlama 3.3 70B InstructTies
Coding51
Intelligence20
Agentic work11
Reasoning60
Math60
Knowledge41
General126
All shared boards369
CodingLike-for-likeSix of these boards feed the Vibe Coding Index51
Coding benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
AA Coding Index11.111.9Llama 3.3 70B Instruct
LiveCodeBench (Vals AI)42.7%Not measuredOnly GPT-4.1 Nano measured
LiveCodeBench (Artificial Analysis run)32.6%28.8%GPT-4.1 Nano
Terminal-Bench Hard (Artificial Analysis run)3.8%3.0%GPT-4.1 Nano
WeirdML19.0%14.4%GPT-4.1 Nano
LMArena Text: coding13061268GPT-4.1 Nano
LMArena Text: software and IT13051273GPT-4.1 Nano
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
AA Intelligence Index7.87.7GPT-4.1 Nano
Epoch Capabilities Index129.5127.3GPT-4.1 Nano
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
τ²-Bench Telecom17.3%26.6%Llama 3.3 70B Instruct
BALROGNot measured23.0%Only Llama 3.3 70B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)33.1%31.9%GPT-4.1 Nano
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
GPQA Diamond50.8%Not measuredOnly GPT-4.1 Nano measured
MMMU Pro (Vals AI)55.0%Not measuredOnly GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)51.2%49.8%GPT-4.1 Nano
Humanity's Last Exam (Artificial Analysis run)3.8%3.6%GPT-4.1 Nano
GPQA Diamond (Epoch AI run)48.9%47.4%GPT-4.1 Nano
ARC-AGI0.0%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Nano measured
SimpleBenchNot measured19.9%Only Llama 3.3 70B Instruct measured
Chess puzzles0.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: hard prompts12861257GPT-4.1 Nano
LMArena Text: expert12711225GPT-4.1 Nano
LMArena Text: hard prompts in English12931277GPT-4.1 Nano
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
AIME26.5%Not measuredOnly GPT-4.1 Nano measured
MATH 500 (Vals AI)80.2%Not measuredOnly GPT-4.1 Nano measured
MGSM (Vals AI)69.3%Not measuredOnly GPT-4.1 Nano measured
AA Math Index24.07.7GPT-4.1 Nano
AIME 2025 (Artificial Analysis run)24.0%7.7%GPT-4.1 Nano
OTIS Mock AIME28.9%5.1%GPT-4.1 Nano
MATH level 570.0%41.6%GPT-4.1 Nano
LMArena Text: math12741267GPT-4.1 Nano
LMArena Text: mathematical work12741267GPT-4.1 Nano
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
MMLU Pro63.5%Not measuredOnly GPT-4.1 Nano measured
LegalBench (Vals AI)61.1%Not measuredOnly GPT-4.1 Nano measured
CorpFin (Vals AI)42.1%Not measuredOnly GPT-4.1 Nano measured
TaxEval (Vals AI)60.8%Not measuredOnly GPT-4.1 Nano measured
MortgageTax (Vals AI)52.8%Not measuredOnly GPT-4.1 Nano measured
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)65.7%71.3%Llama 3.3 70B Instruct
SimpleQA Verified6.0%Not measuredOnly GPT-4.1 Nano measured
MMLUNot measured86.3%Only Llama 3.3 70B Instruct measured
LMArena Text: science12971284GPT-4.1 Nano
LMArena Text: medicine and healthcare12761275GPT-4.1 Nano
LMArena Text: legal and government13001284GPT-4.1 Nano
LMArena Text: business and finance12671243GPT-4.1 Nano
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
Design Arena: websites973Not measuredOnly GPT-4.1 Nano measured
Design Arena: UI components913Not measuredOnly GPT-4.1 Nano measured
Design Arena: game dev970Not measuredOnly GPT-4.1 Nano measured
Design Arena: data viz891Not measuredOnly GPT-4.1 Nano measured
Design Arena: 3D924Not measuredOnly GPT-4.1 Nano measured
Design Arena: all code categories962Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index126
General benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 3.3 70B InstructLeader
IFBench32.0%47.1%Llama 3.3 70B Instruct
Long context reasoning (AA-LCR)20.3%15.7%GPT-4.1 Nano
DTBench52.5%59.5%Llama 3.3 70B Instruct
LMCA5.5%17.5%Llama 3.3 70B Instruct
Fiction.LiveBench25.0%33.3%Llama 3.3 70B Instruct
LMArena Text12851274GPT-4.1 Nano
LMArena Text: instruction following12661242GPT-4.1 Nano
LMArena Text: creative writing12601250GPT-4.1 Nano
LMArena Vision1063Not measuredOnly GPT-4.1 Nano measured
LMArena Text: English13031303Llama 3.3 70B Instruct
LMArena Text: non-English12601236GPT-4.1 Nano
LMArena Text: Chinese12701217GPT-4.1 Nano
LMArena Text: German12881251GPT-4.1 Nano
LMArena Text: Japanese11981150GPT-4.1 Nano
LMArena Text: KoreanNot measured1142Only Llama 3.3 70B Instruct measured
LMArena Text: FrenchNot measured1282Only Llama 3.3 70B Instruct measured
LMArena Text: SpanishNot measured1269Only Llama 3.3 70B Instruct measured
LMArena Text: Russian12611252GPT-4.1 Nano
LMArena Text: PolishNot measured1259Only Llama 3.3 70B Instruct measured
LMArena Text: multi-turn12771280Llama 3.3 70B Instruct
LMArena Text: longer queries12831255GPT-4.1 Nano
LMArena Text: writing and language12611255GPT-4.1 Nano
LMArena Text: entertainment and media12431241GPT-4.1 Nano
LMArena Vision: English1101Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Nano and Llama 3.3 70B Instruct
BenchmarkGPT-4.1 NanoLlama 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

GPT-4.1 Nano$0.0003Fits in one request
Llama 3.3 70B Instruct$0.0008Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
Llama 3.3 70B Instruct$0.025Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
Llama 3.3 70B Instruct$0.097Exceeds the context window

GPT-4.1 Nano 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 GPT-4.1 Nano and Llama 3.3 70B Instruct
SpecificationOpenAI GPT-4.1 NanoMeta Llama 3.3 70B Instruct
MakerOpenAIMeta Llama
WeightsNo public weights listedOpen weights
ReleasedApril 14, 2025December 6, 2024
Context window1.05M131K
Input $/Mtok$0.10$0.45
Output $/Mtok$0.40$0.72
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano better than Llama 3.3 70B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 1.8x cheaper ($0.40 vs $0.72 per million) and a larger context window (1.05M against 131K tokens).

Which is cheaper, GPT-4.1 Nano or Llama 3.3 70B Instruct?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Llama 3.3 70B Instruct costs $0.45 and $0.72. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4.1 Nano or Llama 3.3 70B Instruct?

GPT-4.1 Nano, with 1.05M tokens against 131K.

How many benchmarks is the GPT-4.1 Nano vs Llama 3.3 70B Instruct comparison based on?

45 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Nano's coding index rests on 0 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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