GPT-5.6 Luna vs Nemotron 3.5 Lightning

GPT-5.6 Luna leads Nemotron 3.5 Lightning on coding, 58.0 to 22.6 on the Vibe Coding Index, and Nemotron 3.5 Lightning costs 8.2x less per output token ($0.147 vs $1.20 per million). Updated October 22, 2026; 20 benchmarks have a result for both.

Replace GPT-5.6 Luna Replace Nemotron 3.5 Lightning

GPT-5.6 LunaOpenAI

Coding: 58.0
Overall: 61.6
Output $/M: $1.20

Nemotron 3.5 LightningNVIDIA

Coding: 22.6
Overall: No data
Output $/M: $0.147

vs boards won of 20 shared, 1 tied

GPT-5.6 Luna or Nemotron 3.5 Lightning: which to pick

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 22.6 for Nemotron 3.5 Lightning.

Pick Nemotron 3.5 Lightning for output tokens 8.2x cheaper ($0.147 vs $1.20 per million).

Model AGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task Model BNemotron 3.5 LightningNVIDIA22.6/1002 independent benchmarks$0.06 per solved task

20100

Shared results: 20
GPT-5.6 Luna only: 100
Nemotron 3.5 Lightning only: 0
Like-for-like categories: 6 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
GPT-5.6 Luna
GPT-5.6 Luna scores 58.0 against 22.6.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 12.9.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 42.1 against 3.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Luna has a GPQA Diamond result, 91.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Luna has a MMLU Pro result, 86.0%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.6 Luna has a Design Arena: websites result, 1255.
Directional only
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Lightning
GPT-5.6 Luna $0.0008, Nemotron 3.5 Lightning $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Luna
GPT-5.6 Luna $0.04, Nemotron 3.5 Lightning $0.06.
Published attempt cost and pass rate

At a glance

Coding index: GPT-5.6 Luna 58.0 from 6 benchmarks, Nemotron 3.5 Lightning 22.6 from 2 benchmarks.
Widest category: General, 51.7 points apart on average over 2 shared benchmarks.
Widest single gap: MedScribe (Vals AI): GPT-5.6 Luna 84.4% against Nemotron 3.5 Lightning 4.3%, 80.1 points apart on a 0 to 100 scale.
Output price: GPT-5.6 Luna $1.20 against Nemotron 3.5 Lightning $0.147 per million output tokens, 8.2x apart.
Context window: GPT-5.6 Luna takes 1.05M tokens, Nemotron 3.5 Lightning 262K.

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	GPT-5.6 Luna	Ties
Coding	8	1 tie
Intelligence	1
Agentic work	5
Reasoning	2
Knowledge	1
General	2
All shared boards	19	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index80

Coding benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
LiveBench coding	73.6%	Not measured	Only GPT-5.6 Luna measured
LMArena WebDev	1518	Not measured	Only GPT-5.6 Luna measured
AA Coding Index	71.4	26.8	GPT-5.6 Luna
SWE-bench Verified (Vals AI)	93.0%	52.8%	GPT-5.6 Luna
Terminal-Bench 4 (Vals AI)	11.6%	Not measured	Only GPT-5.6 Luna measured
Vibe Code Bench (Vals AI)	77.1%	0.0%	GPT-5.6 Luna
Code migration (Vals AI)	44.5%	3.0%	GPT-5.6 Luna
ProgramBench (Vals AI)	0.0%	0.0%	Tie
IOI (Vals AI)	61.8%	Not measured	Only GPT-5.6 Luna measured
Terminal-Bench 2.1 (Vals AI)	79.0%	10.9%	GPT-5.6 Luna
Vibe Code Bench 1-100 (Vals AI)	22.6%	Not measured	Only GPT-5.6 Luna measured
SkillsBench (Vals AI)	60.5%	Not measured	Only GPT-5.6 Luna measured
CyberBench (Vals AI)	73.6%	29.5%	GPT-5.6 Luna
SciCode	53.6%	32.1%	GPT-5.6 Luna
FrontierCode	39.8%	Not measured	Only GPT-5.6 Luna measured
WeirdML	60.9%	Not measured	Only GPT-5.6 Luna measured
ALE-Bench	1667.4	769.2	GPT-5.6 Luna
LMArena Text: coding	1466	Not measured	Only GPT-5.6 Luna measured
LMArena Text: software and IT	1463	Not measured	Only GPT-5.6 Luna measured
LMArena WebDev: React	1508	Not measured	Only GPT-5.6 Luna measured
LMArena WebDev: HTML	1520	Not measured	Only GPT-5.6 Luna measured
LMArena WebDev: from an image	1517	Not measured	Only GPT-5.6 Luna measured
SciCode	6.2%	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 20 boards here

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

Intelligence benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
AA Intelligence Index	37.3	12.9	GPT-5.6 Luna
Epoch Capabilities Index	156.5	Not measured	Only GPT-5.6 Luna measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index50

Agentic work benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
AA Agentic Index	42.1	3.5	GPT-5.6 Luna
LiveBench research	51.0%	Not measured	Only GPT-5.6 Luna measured
LiveBench browser	68.0%	Not measured	Only GPT-5.6 Luna measured
LiveBench long agentic	30.4%	Not measured	Only GPT-5.6 Luna measured
SREBench (Vals AI)	1.5%	Not measured	Only GPT-5.6 Luna measured
Finance Agent (Vals AI)	55.0%	18.5%	GPT-5.6 Luna
Tax Agent Bench (Vals AI)	24.8%	2.6%	GPT-5.6 Luna
Legal Research Bench (Vals AI)	36.5%	2.9%	GPT-5.6 Luna
Excel Modeling Benchmark (Vals AI)	67.1%	17.0%	GPT-5.6 Luna
BioMysteryBench (Vals AI)	61.5%	Not measured	Only GPT-5.6 Luna measured
Terminal-Bench-Science (Vals AI)	0.0%	Not measured	Only GPT-5.6 Luna measured
Vals Science Index	25.3%	Not measured	Only GPT-5.6 Luna measured
APEX-Agents	43.0%	Not measured	Only GPT-5.6 Luna measured
BALROG	45.6%	Not measured	Only GPT-5.6 Luna measured
Vending-Bench 2	$4,095	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 27 boards here

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

Reasoning benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
GPQA Diamond	91.7%	Not measured	Only GPT-5.6 Luna measured
LiveBench reasoning	85.6%	Not measured	Only GPT-5.6 Luna measured
MysteryMechanism (Vals AI)	14.4%	Not measured	Only GPT-5.6 Luna measured
MMMU Pro (Vals AI)	85.0%	Not measured	Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)	91.1%	74.3%	GPT-5.6 Luna
Humanity's Last Exam (Artificial Analysis run)	39.5%	10.6%	GPT-5.6 Luna
GPQA Diamond (Epoch AI run)	91.6%	Not measured	Only GPT-5.6 Luna measured
ARC-AGI	88.0%	Not measured	Only GPT-5.6 Luna measured
ARC-AGI-2	59.5%	Not measured	Only GPT-5.6 Luna measured
SimpleBench	46.8%	Not measured	Only GPT-5.6 Luna measured
Chess puzzles	43.0%	Not measured	Only GPT-5.6 Luna measured
Mystery game puzzles	21.0%	Not measured	Only GPT-5.6 Luna measured
LMArena Text: hard prompts	1451	Not measured	Only GPT-5.6 Luna measured
LMArena Text: expert	1478	Not measured	Only GPT-5.6 Luna measured
LMArena Text: hard prompts in English	1460	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: diagrams	1273	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: homework	1282	Not measured	Only GPT-5.6 Luna measured
Kagi LLM Benchmark	49.1%	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 5 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared

Math benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
OTIS Mock AIME	98.3%	Not measured	Only GPT-5.6 Luna measured
FrontierMath, tiers 1 to 3	82.1%	Not measured	Only GPT-5.6 Luna measured
FrontierMath, tier 4	61.0%	Not measured	Only GPT-5.6 Luna measured
ProofBench	60.0%	Not measured	Only GPT-5.6 Luna measured
LMArena Text: math	1459	Not measured	Only GPT-5.6 Luna measured
LMArena Text: mathematical work	1470	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 8 boards here

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

Knowledge benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
MMLU Pro	86.0%	Not measured	Only GPT-5.6 Luna measured
LegalBench (Vals AI)	84.0%	Not measured	Only GPT-5.6 Luna measured
CorpFin (Vals AI)	64.2%	54.2%	GPT-5.6 Luna
TaxEval (Vals AI)	76.2%	Not measured	Only GPT-5.6 Luna measured
MortgageTax (Vals AI)	67.3%	Not measured	Only GPT-5.6 Luna measured
MedCode (Vals AI)	42.4%	Not measured	Only GPT-5.6 Luna measured
SimpleQA Verified	41.0%	Not measured	Only GPT-5.6 Luna measured
LMArena Text: science	1433	Not measured	Only GPT-5.6 Luna measured
LMArena Text: medicine and healthcare	1399	Not measured	Only GPT-5.6 Luna measured
LMArena Text: legal and government	1446	Not measured	Only GPT-5.6 Luna measured
LMArena Text: business and finance	1439	Not measured	Only GPT-5.6 Luna measured
FACTS Benchmark Suite	35.0%	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 8 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared

Web design benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
Design Arena: websites	1255	Not measured	Only GPT-5.6 Luna measured
Design Arena: UI components	1248	Not measured	Only GPT-5.6 Luna measured
Design Arena: game dev	1195	Not measured	Only GPT-5.6 Luna measured
Design Arena: data viz	1212	Not measured	Only GPT-5.6 Luna measured
Design Arena: 3D	1121	Not measured	Only GPT-5.6 Luna measured
Design Arena: all code categories	1230	Not measured	Only GPT-5.6 Luna measured
Design Arena: SVG	1193	Not measured	Only GPT-5.6 Luna measured
Design Arena: ASCII art	1142	Not measured	Only GPT-5.6 Luna measured
LiveBench design	76.0%	Not measured	Only GPT-5.6 Luna measured

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

General benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	Leader
LiveBench data analysis	78.0%	Not measured	Only GPT-5.6 Luna measured
Public Benefits Bench (Vals AI)	61.2%	Not measured	Only GPT-5.6 Luna measured
SAGE (Vals AI)	44.2%	Not measured	Only GPT-5.6 Luna measured
MedScribe (Vals AI)	84.4%	4.3%	GPT-5.6 Luna
Vals Multimodal Index	69.1%	Not measured	Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)	83.7%	60.3%	GPT-5.6 Luna
DTBench	89.1%	Not measured	Only GPT-5.6 Luna measured
LMCA	48.5%	Not measured	Only GPT-5.6 Luna measured
Surface Evolver Bench	61.9%	Not measured	Only GPT-5.6 Luna measured
Furniture assembly	42.5%	Not measured	Only GPT-5.6 Luna measured
LMArena Text	1431	Not measured	Only GPT-5.6 Luna measured
LMArena Text: instruction following	1437	Not measured	Only GPT-5.6 Luna measured
LMArena Text: creative writing	1396	Not measured	Only GPT-5.6 Luna measured
LMArena Vision	1257	Not measured	Only GPT-5.6 Luna measured
LMArena Text: English	1441	Not measured	Only GPT-5.6 Luna measured
LMArena Text: non-English	1417	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Chinese	1470	Not measured	Only GPT-5.6 Luna measured
LMArena Text: German	1455	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Japanese	1415	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Korean	1415	Not measured	Only GPT-5.6 Luna measured
LMArena Text: French	1458	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Spanish	1446	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Russian	1427	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Polish	1405	Not measured	Only GPT-5.6 Luna measured
LMArena Text: multi-turn	1434	Not measured	Only GPT-5.6 Luna measured
LMArena Text: longer queries	1436	Not measured	Only GPT-5.6 Luna measured
LMArena Text: writing and language	1419	Not measured	Only GPT-5.6 Luna measured
LMArena Text: entertainment and media	1402	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: English	1263	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: Chinese	1294	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: reading text	1264	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: humor	1190	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: creative writing	1257	Not measured	Only GPT-5.6 Luna measured
LMArena Document	1457	Not measured	Only GPT-5.6 Luna measured
EQ-Bench 4	1156	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 13 boards here

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

Image generation benchmarks for GPT-5.6 Luna and Nemotron 3.5 Lightning
Benchmark	GPT-5.6 Luna	Nemotron 3.5 Lightning	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

GPT-5.6 Luna$0.0008Fits in one request

Nemotron 3.5 Lightning$0.0001Fits in one request

Nemotron 3.5 Lightning costs less

Repository review

50K input + 3K output tokens

GPT-5.6 Luna$0.014Fits in one request

Nemotron 3.5 Lightning$0.0031Fits in one request

Nemotron 3.5 Lightning costs less

Agent loop

200K input + 10K output tokens

GPT-5.6 Luna$0.052Fits in one request

Nemotron 3.5 Lightning$0.012Fits in one request

Nemotron 3.5 Lightning 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-5.6 Luna and Nemotron 3.5 Lightning
Specification	OpenAI GPT-5.6 Luna	NVIDIA Nemotron 3.5 Lightning
Maker	OpenAI	NVIDIA
Weights	No public weights listed	Open weights
Released	July 9, 2026	August 11, 2026
Context window	1.05M	262K
Input $/Mtok	$0.20	$0.0534
Output $/Mtok	$1.20	$0.147
Coding index	58.0	22.6
Independent measurements behind it	6	2
Cost per solved task	$0.04	$0.06
Source	OpenRouter listing	OpenRouter listing

Questions

Is GPT-5.6 Luna better than Nemotron 3.5 Lightning for coding?

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 22.6 for Nemotron 3.5 Lightning. Pick Nemotron 3.5 Lightning for output tokens 8.2x cheaper ($0.147 vs $1.20 per million).

Which is cheaper, GPT-5.6 Luna or Nemotron 3.5 Lightning?

GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; Nemotron 3.5 Lightning costs $0.0534 and $0.147. Per solved SWE-bench Verified task, GPT-5.6 Luna costs $0.04 and Nemotron 3.5 Lightning $0.06.

Which has the bigger context window, GPT-5.6 Luna or Nemotron 3.5 Lightning?

GPT-5.6 Luna, with 1.05M tokens against 262K.

How many benchmarks is the GPT-5.6 Luna vs Nemotron 3.5 Lightning comparison based on?

20 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Luna's coding index rests on 6 independent benchmarks and Nemotron 3.5 Lightning's on 2. Where only one model has a result, the page says so instead of naming a winner.

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GPT-5.6 Luna or Nemotron 3.5 Lightning: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next