GPT-6 Luna vs Sonar Deep Research
GPT-6 Luna costs 16.0x less per output token than Sonar Deep Research ($0.50 vs $8.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
GPT-6 LunaOpenAI
- Coding
- 57.3
- Overall
- 38.1
- Output $/M
- $0.50
Sonar Deep ResearchPerplexity
- Coding
- No data
- Overall
- No data
- Output $/M
- $8.00
vs $0.50 vs $8.00 per 1M output tokens. GPT-6 Luna is 16.0x cheaper.
GPT-6 Luna or Sonar Deep Research: which to pick
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; Sonar Deep Research has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
Model AGPT-6 LunaOpenAI57.3/1005 independent benchmarksNo cost per solved taskModel BSonar Deep ResearchPerplexityNot benchmarkedNo coding benchmarkNo cost per solved task
No benchmark has tested both yet. GPT-6 Luna has results on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI); Sonar Deep Research has none yet. Compare them on price and context instead.
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
Only GPT-6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-6 Luna has a AA Intelligence Index result, 38.1.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6 Luna has a Design Arena: websites result, 1272.
Directional only
General
Vals Index
No call
Only GPT-6 Luna has a Vals Index result, 52.3%.
Directional only
Long documents
Listed context window
GPT-6 Luna
GPT-6 Luna takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6 Luna
GPT-6 Luna $0.0003, Sonar Deep Research $0.0060 per turn.
List prices
At a glance
- Coding index
- GPT-6 Luna 57.3 from 5 benchmarks, Sonar Deep Research not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-6 Luna $0.50 against Sonar Deep Research $8.00 per million output tokens, 16.0x apart.
- Context window
- GPT-6 Luna takes 1.05M tokens, Sonar Deep Research 128K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| LiveBench coding | 84.5% | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev | 1578 | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench 4 (Vals AI) | 13.6% | Not measured | Only GPT-6 Luna measured |
| Vibe Code Bench (Vals AI) | 81.7% | Not measured | Only GPT-6 Luna measured |
| Code migration (Vals AI) | 42.5% | Not measured | Only GPT-6 Luna measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-6 Luna measured |
| IOI (Vals AI) | 55.6% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 73.0% | Not measured | Only GPT-6 Luna measured |
| SWE-bench Multimodal (Vals AI) | 37.5% | Not measured | Only GPT-6 Luna measured |
| CyberBench (Vals AI) | 76.3% | Not measured | Only GPT-6 Luna measured |
| SciCode | 54.6% | Not measured | Only GPT-6 Luna measured |
| FrontierCode | 42.4% | Not measured | Only GPT-6 Luna measured |
| ALE-Bench | 1576.9 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: coding | 1437 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: software and IT | 1423 | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev: React | 1573 | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev: HTML | 1595 | Not measured | Only GPT-6 Luna measured |
| LMArena WebDev: from an image | 1571 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.1 | Not measured | Only GPT-6 Luna measured |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-6 Luna measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1191 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building full-stack apps | 1158 | Not measured | Only GPT-6 Luna measured |
| Design Arena: agents building mobile apps | 1128 | Not measured | Only GPT-6 Luna measured |
| LiveBench research | 43.5% | Not measured | Only GPT-6 Luna measured |
| LiveBench browser | 72.0% | Not measured | Only GPT-6 Luna measured |
| LiveBench long agentic | 48.1% | Not measured | Only GPT-6 Luna measured |
| SREBench (Vals AI) | 2.7% | Not measured | Only GPT-6 Luna measured |
| Finance Agent (Vals AI) | 49.9% | Not measured | Only GPT-6 Luna measured |
| Tax Agent Bench (Vals AI) | 19.9% | Not measured | Only GPT-6 Luna measured |
| Legal Research Bench (Vals AI) | 30.3% | Not measured | Only GPT-6 Luna measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 4.2% | Not measured | Only GPT-6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | 68.5% | Not measured | Only GPT-6 Luna measured |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only GPT-6 Luna measured |
| Vals Science Index | 28.4% | Not measured | Only GPT-6 Luna measured |
| APEX-Agents | 44.3% | Not measured | Only GPT-6 Luna measured |
| SpireClimb | 0.0% | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| LiveBench reasoning | 81.8% | Not measured | Only GPT-6 Luna measured |
| MysteryMechanism (Vals AI) | 19.4% | Not measured | Only GPT-6 Luna measured |
| Humanity's Last Exam (Artificial Analysis run) | 38.5% | Not measured | Only GPT-6 Luna measured |
| GPQA Diamond (Epoch AI run) | 90.5% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI | 86.7% | Not measured | Only GPT-6 Luna measured |
| ARC-AGI-2 | 59.3% | Not measured | Only GPT-6 Luna measured |
| Chess puzzles | 36.0% | Not measured | Only GPT-6 Luna measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: hard prompts | 1410 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: expert | 1442 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: hard prompts in English | 1410 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: diagrams | 1245 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: homework | 1261 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tiers 1 to 3 | 78.9% | Not measured | Only GPT-6 Luna measured |
| FrontierMath, tier 4 | 56.1% | Not measured | Only GPT-6 Luna measured |
| ProofBench | 64.0% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: math | 1409 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: mathematical work | 1427 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 44.7% | Not measured | Only GPT-6 Luna measured |
| SimpleQA Verified | 41.4% | Not measured | Only GPT-6 Luna measured |
| LMArena Text: science | 1386 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: medicine and healthcare | 1352 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: legal and government | 1400 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: business and finance | 1388 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| Design Arena: websites | 1272 | Not measured | Only GPT-6 Luna measured |
| Design Arena: UI components | 1297 | Not measured | Only GPT-6 Luna measured |
| Design Arena: game dev | 1260 | Not measured | Only GPT-6 Luna measured |
| Design Arena: data viz | 1215 | Not measured | Only GPT-6 Luna measured |
| Design Arena: 3D | 1217 | Not measured | Only GPT-6 Luna measured |
| Design Arena: all code categories | 1271 | Not measured | Only GPT-6 Luna measured |
| Design Arena: SVG | 1251 | Not measured | Only GPT-6 Luna measured |
| Design Arena: ASCII art | 1153 | Not measured | Only GPT-6 Luna measured |
| LiveBench design | 82.5% | Not measured | Only GPT-6 Luna measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards measured
| Benchmark | GPT-6 Luna | Sonar Deep Research | Leader |
|---|---|---|---|
| Vals Index | 52.3% | Not measured | Only GPT-6 Luna measured |
| LiveBench data analysis | 73.4% | Not measured | Only GPT-6 Luna measured |
| Public Benefits Bench (Vals AI) | 57.6% | Not measured | Only GPT-6 Luna measured |
| SAGE (Vals AI) | 48.1% | Not measured | Only GPT-6 Luna measured |
| MedScribe (Vals AI) | 83.7% | Not measured | Only GPT-6 Luna measured |
| Long context reasoning (AA-LCR) | 83.3% | Not measured | Only GPT-6 Luna measured |
| DTBench | 90.1% | Not measured | Only GPT-6 Luna measured |
| LMCA | 44.5% | Not measured | Only GPT-6 Luna measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-6 Luna measured |
| LMArena Text | 1389 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: instruction following | 1408 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: creative writing | 1363 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision | 1216 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: English | 1393 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: non-English | 1381 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Chinese | 1427 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: German | 1376 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Japanese | 1369 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Korean | 1359 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: French | 1408 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Spanish | 1391 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Russian | 1392 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: Polish | 1383 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: multi-turn | 1392 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: longer queries | 1408 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: writing and language | 1384 | Not measured | Only GPT-6 Luna measured |
| LMArena Text: entertainment and media | 1364 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: English | 1204 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: Chinese | 1266 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: reading text | 1225 | Not measured | Only GPT-6 Luna measured |
| LMArena Vision: creative writing | 1205 | Not measured | Only GPT-6 Luna measured |
| Neither model has a result on the other 15 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-6 Luna$0.0003Fits in one request
Sonar Deep Research$0.0060Fits in one request
GPT-6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-6 Luna$0.0065Fits in one request
Sonar Deep Research$0.124Fits in one request
GPT-6 Luna costs less
Agent loop
200K input + 10K output tokens
GPT-6 Luna$0.025Fits in one request
Sonar Deep Research$0.480Exceeds the context window
GPT-6 Luna 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.
| Specification | OpenAI GPT-6 Luna | Perplexity Sonar Deep Research |
|---|---|---|
| Maker | OpenAI | Perplexity |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | March 7, 2025 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $0.10 | $2.00 |
| Output $/Mtok | $0.50 | $8.00 |
| Coding index | 57.3 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Luna better than Sonar Deep Research for coding?
Only GPT-6 Luna has a coding score, 57.3 on the Vibe Coding Index; Sonar Deep Research has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-6 Luna or Sonar Deep Research?
GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; Sonar Deep Research costs $2.00 and $8.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Luna or Sonar Deep Research?
GPT-6 Luna, with 1.05M tokens against 128K.
Has any benchmark tested both GPT-6 Luna and Sonar Deep Research?
No benchmark has tested both yet. GPT-6 Luna has results on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI); Sonar Deep Research has none yet. Compare them on price and context instead. Data as of October 21, 2026.