Nova Premier 1.0 vs Llama 3.3 70B Instruct

Nova Premier 1.0 leads Llama 3.3 70B Instruct on the Artificial Analysis Intelligence Index, 9.2 to 7.7, and Llama 3.3 70B Instruct costs 17.4x less per output token ($0.72 vs $12.50 per million). Updated October 21, 2026; 11 benchmarks have a result for both.

Replace Nova Premier 1.0 Replace Llama 3.3 70B Instruct

Nova Premier 1.0Amazon

Coding: No data
Overall: No data
Output $/M: $12.50

Llama 3.3 70B InstructMeta Llama

Coding: No data
Overall: 26.0
Output $/M: $0.72

vs boards won of 11 shared

Nova Premier 1.0 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 Nova Premier 1.0 for a larger context window (1M against 131K tokens) and work measured by IFBench, where it leads.

Model ANova Premier 1.0AmazonNot benchmarkedNo coding benchmarkNo cost per solved task Model BLlama 3.3 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task

11341

Shared results: 11
Nova Premier 1.0 only: 3
Llama 3.3 70B Instruct only: 41
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.

Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Nova Premier 1.0
Nova Premier 1.0 leads, 9.2 against 7.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only Nova Premier 1.0 has a Design Arena: websites result, 835.
Directional only
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.3 70B Instruct
Nova Premier 1.0 $0.0088, Llama 3.3 70B Instruct $0.0008 per turn.
List prices

At a glance

Coding index: Nova Premier 1.0 not benchmarked, Llama 3.3 70B Instruct not benchmarked.
Widest category: General, 14.8 points apart on average over 2 shared benchmarks.
Widest single gap: Long context reasoning (AA-LCR): Nova Premier 1.0 34.3% against Llama 3.3 70B Instruct 15.7%, 18.7 points apart on a 0 to 100 scale.
Output price: Nova Premier 1.0 $12.50 against Llama 3.3 70B Instruct $0.72 per million output tokens, 17.4x apart.
Context window: Nova Premier 1.0 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
Category	Nova Premier 1.0	Llama 3.3 70B Instruct
Coding	2	0
Intelligence	1	0
Agentic work	1	0
Reasoning	2	0
Math	2	0
Knowledge	1	0
General	1	1
All shared boards	10	1

CodingLike-for-likeSix of these boards feed the Vibe Coding Index20

Coding benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
AA Coding Index	Not measured	11.9	Only Llama 3.3 70B Instruct measured
LiveCodeBench (Artificial Analysis run)	31.7%	28.8%	Nova Premier 1.0
Terminal-Bench Hard (Artificial Analysis run)	6.8%	3.0%	Nova Premier 1.0
WeirdML	Not measured	14.4%	Only Llama 3.3 70B Instruct measured
ALE-Bench	147.4	Not measured	Only Nova Premier 1.0 measured
LMArena Text: coding	Not measured	1268	Only Llama 3.3 70B Instruct measured
LMArena Text: software and IT	Not measured	1273	Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 32 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10

Intelligence benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
AA Intelligence Index	9.2	7.7	Nova Premier 1.0
Epoch Capabilities Index	Not measured	127.3	Only Llama 3.3 70B Instruct measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index10

Agentic work benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
τ²-Bench Telecom	38.3%	26.6%	Nova Premier 1.0
BALROG	Not measured	23.0%	Only Llama 3.3 70B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)	Not measured	31.9%	Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 38 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index20

Reasoning benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
GPQA Diamond (Artificial Analysis run)	56.9%	49.8%	Nova Premier 1.0
Humanity's Last Exam (Artificial Analysis run)	4.2%	3.6%	Nova Premier 1.0
GPQA Diamond (Epoch AI run)	Not measured	47.4%	Only Llama 3.3 70B Instruct measured
SimpleBench	Not measured	19.9%	Only Llama 3.3 70B Instruct measured
LMArena Text: hard prompts	Not measured	1257	Only Llama 3.3 70B Instruct measured
LMArena Text: expert	Not measured	1225	Only Llama 3.3 70B Instruct measured
LMArena Text: hard prompts in English	Not measured	1277	Only Llama 3.3 70B Instruct measured
Kagi LLM Benchmark	44.8%	Not measured	Only Nova Premier 1.0 measured
Neither model has a result on the other 14 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index20

Math benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
AA Math Index	17.3	7.7	Nova Premier 1.0
AIME 2025 (Artificial Analysis run)	17.3%	7.7%	Nova Premier 1.0
OTIS Mock AIME	Not measured	5.1%	Only Llama 3.3 70B Instruct measured
MATH level 5	Not measured	41.6%	Only Llama 3.3 70B Instruct measured
LMArena Text: math	Not measured	1267	Only Llama 3.3 70B Instruct measured
LMArena Text: mathematical work	Not measured	1267	Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10

Knowledge benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
MMLU Pro (Artificial Analysis run)	73.3%	71.3%	Nova Premier 1.0
MMLU	Not measured	86.3%	Only Llama 3.3 70B Instruct measured
LMArena Text: science	Not measured	1284	Only Llama 3.3 70B Instruct measured
LMArena Text: medicine and healthcare	Not measured	1275	Only Llama 3.3 70B Instruct measured
LMArena Text: legal and government	Not measured	1284	Only Llama 3.3 70B Instruct measured
LMArena Text: business and finance	Not measured	1243	Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 12 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared

Web design benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
Design Arena: websites	835	Not measured	Only Nova Premier 1.0 measured
Neither model has a result on the other 8 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index11

General benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
IFBench	36.2%	47.1%	Llama 3.3 70B Instruct
Long context reasoning (AA-LCR)	34.3%	15.7%	Nova Premier 1.0
DTBench	Not measured	59.5%	Only Llama 3.3 70B Instruct measured
LMCA	Not measured	17.5%	Only Llama 3.3 70B Instruct measured
Fiction.LiveBench	Not measured	33.3%	Only Llama 3.3 70B Instruct measured
LMArena Text	Not measured	1274	Only Llama 3.3 70B Instruct measured
LMArena Text: instruction following	Not measured	1242	Only Llama 3.3 70B Instruct measured
LMArena Text: creative writing	Not measured	1250	Only Llama 3.3 70B Instruct measured
LMArena Text: English	Not measured	1303	Only Llama 3.3 70B Instruct measured
LMArena Text: non-English	Not measured	1236	Only Llama 3.3 70B Instruct measured
LMArena Text: Chinese	Not measured	1217	Only Llama 3.3 70B Instruct measured
LMArena Text: German	Not measured	1251	Only Llama 3.3 70B Instruct measured
LMArena Text: Japanese	Not measured	1150	Only Llama 3.3 70B Instruct measured
LMArena Text: Korean	Not measured	1142	Only Llama 3.3 70B Instruct measured
LMArena Text: French	Not measured	1282	Only Llama 3.3 70B Instruct measured
LMArena Text: Spanish	Not measured	1269	Only Llama 3.3 70B Instruct measured
LMArena Text: Russian	Not measured	1252	Only Llama 3.3 70B Instruct measured
LMArena Text: Polish	Not measured	1259	Only Llama 3.3 70B Instruct measured
LMArena Text: multi-turn	Not measured	1280	Only Llama 3.3 70B Instruct measured
LMArena Text: longer queries	Not measured	1255	Only Llama 3.3 70B Instruct measured
LMArena Text: writing and language	Not measured	1255	Only Llama 3.3 70B Instruct measured
LMArena Text: entertainment and media	Not measured	1241	Only Llama 3.3 70B Instruct measured
Neither model has a result on the other 24 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for Nova Premier 1.0 and Llama 3.3 70B Instruct
Benchmark	Nova Premier 1.0	Llama 3.3 70B Instruct	Leader
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

Nova Premier 1.0$0.0088Fits 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

Nova Premier 1.0$0.163Fits 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

Nova Premier 1.0$0.625Fits 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 Nova Premier 1.0 and Llama 3.3 70B Instruct
Specification	Amazon Nova Premier 1.0	Meta Llama 3.3 70B Instruct
Maker	Amazon	Meta Llama
Weights	No public weights listed	Open weights
Released	October 31, 2025	December 6, 2024
Context window	1M	131K
Input $/Mtok	$2.50	$0.45
Output $/Mtok	$12.50	$0.72
Coding index	Not benchmarked	Not benchmarked
Independent measurements behind it	0	0
Cost per solved task	Not computable	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Nova Premier 1.0 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 Nova Premier 1.0 for a larger context window (1M against 131K tokens) and work measured by IFBench, where it leads.

Which is cheaper, Nova Premier 1.0 or Llama 3.3 70B Instruct?

Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 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, Nova Premier 1.0 or Llama 3.3 70B Instruct?

Nova Premier 1.0, with 1M tokens against 131K.

How many benchmarks is the Nova Premier 1.0 vs Llama 3.3 70B Instruct comparison based on?

11 benchmarks have a result for both models as of October 21, 2026. Nova Premier 1.0'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.

Nova Premier 1.0 or Llama 3.3 70B Instruct: which to pick

Which one for your work

Coding

Intelligence

Web design

Long documents

Everyday cost

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

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