R1 0528 vs GPT-6 Sol
GPT-6 Sol leads R1 0528 on the Artificial Analysis Intelligence Index, 47.6 to 13.1, and R1 0528 costs 4.6x less per output token ($2.18 vs $10.00 per million). Updated October 22, 2026; 45 benchmarks have a result for both.
R1 0528 or GPT-6 Sol: which to pick
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding.
Pick R1 0528 for output tokens 4.6x cheaper ($2.18 vs $10.00 per million) and work measured by LMArena Text: software and IT or LMArena Text: hard prompts in English, where it leads.
- Shared results
- 45
- R1 0528 only
- 18
- GPT-6 Sol only
- 59
- 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
Only GPT-6 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 13.1.
Same board, both measured
Web design
Design Arena: websites
GPT-6 Sol
GPT-6 Sol leads, 1293 against 1149.
Same board, both measured
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
R1 0528
R1 0528 $0.0016, GPT-6 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- R1 0528 not benchmarked, GPT-6 Sol 76.0 from 5 benchmarks.
- Widest category
- Intelligence, 34.5 points apart on average over 1 shared benchmark.
- Widest single gap
- ARC-AGI-2: R1 0528 1.1% against GPT-6 Sol 89.6%, 88.5 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.18 against GPT-6 Sol $10.00 per million output tokens, 4.6x apart.
- Context window
- R1 0528 takes 164K tokens, GPT-6 Sol 1.05M.
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.
| Category | R1 0528 | Bars | GPT-6 Sol | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 1 | 6 | ||
| Math | 0 | 4 | ||
| Knowledge | 4 | 1 | ||
| Web design | 0 | 7 | ||
| General | 14 | 4 | ||
| All shared boards | 20 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | Not measured | Only R1 0528 measured |
| LiveBench coding | Not measured | 93.1% | Only GPT-6 Sol measured |
| LMArena WebDev | Not measured | 1683 | Only GPT-6 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 44.4% | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 87.8% | Only GPT-6 Sol measured |
| Code migration (Vals AI) | Not measured | 57.2% | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only GPT-6 Sol measured |
| IOI (Vals AI) | Not measured | 82.6% | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 83.2% | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | Not measured | 78.0% | Only GPT-6 Sol measured |
| LiveCodeBench (Artificial Analysis run) | 77.0% | Not measured | Only R1 0528 measured |
| SciCode | Not measured | 57.6% | Only GPT-6 Sol measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only R1 0528 measured |
| FrontierCode | Not measured | 49.3% | Only GPT-6 Sol measured |
| WeirdML | 41.6% | Not measured | Only R1 0528 measured |
| ALE-Bench | 804.1 | 2462.0 | GPT-6 Sol |
| LMArena Text: coding | 1427 | 1448 | GPT-6 Sol |
| LMArena Text: software and IT | 1435 | 1433 | R1 0528 |
| LMArena WebDev: React | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: from an image | Not measured | 1660 | Only GPT-6 Sol measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 47.6 | GPT-6 Sol |
| Epoch Capabilities Index | Not measured | 163.7 | Only GPT-6 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1231 | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1237 | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1217 | Only GPT-6 Sol measured |
| LiveBench research | Not measured | 69.3% | Only GPT-6 Sol measured |
| LiveBench browser | Not measured | 92.0% | Only GPT-6 Sol measured |
| LiveBench long agentic | Not measured | 66.9% | Only GPT-6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 49.0% | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.0% | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 28.9% | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.5% | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 74.8% | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 30.0% | Only GPT-6 Sol measured |
| Vals Science Index | Not measured | 45.0% | Only GPT-6 Sol measured |
| τ²-Bench Telecom | 36.5% | Not measured | Only R1 0528 measured |
| APEX-Agents | Not measured | 54.3% | Only GPT-6 Sol measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| SpireClimb | Not measured | 7.5% | Only GPT-6 Sol measured |
| Vending-Bench 2 | Not measured | $14,428 | Only GPT-6 Sol measured |
| BrowseComp-Plus | 16.4% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 30.2% | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 81.3% | Not measured | Only R1 0528 measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 47.9% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | 76.3% | 94.3% | GPT-6 Sol |
| ARC-AGI | 21.2% | 95.5% | GPT-6 Sol |
| ARC-AGI-2 | 1.1% | 89.6% | GPT-6 Sol |
| SimpleBench | 40.8% | Not measured | Only R1 0528 measured |
| Chess puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| Mystery game puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| EBR-bench | Not measured | 53.3% | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1415 | 1422 | GPT-6 Sol |
| LMArena Text: expert | 1394 | 1437 | GPT-6 Sol |
| LMArena Text: hard prompts in English | 1422 | 1420 | R1 0528 |
| LMArena Vision: diagrams | Not measured | 1270 | Only GPT-6 Sol measured |
| LMArena Vision: homework | Not measured | 1286 | Only GPT-6 Sol measured |
| Humanity's Last Exam (Scale run) | Not measured | 33.8% | Only GPT-6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Math Index | 76.0 | Not measured | Only R1 0528 measured |
| AIME 2025 (Artificial Analysis run) | 76.0% | Not measured | Only R1 0528 measured |
| OTIS Mock AIME | 66.4% | 100.0% | GPT-6 Sol |
| FrontierMath, tiers 1 to 3 | Not measured | 89.8% | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | Not measured | 90.0% | Only GPT-6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-6 Sol measured |
| MATH level 5 | 96.6% | Not measured | Only R1 0528 measured |
| LMArena Text: math | 1400 | 1407 | GPT-6 Sol |
| LMArena Text: mathematical work | 1415 | 1424 | GPT-6 Sol |
| MathArena | 12.9% | 80.1% | GPT-6 Sol |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 47.1% | Only GPT-6 Sol measured |
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| SimpleQA Verified | Not measured | 60.7% | Only GPT-6 Sol measured |
| LMArena Text: science | 1430 | 1389 | R1 0528 |
| LMArena Text: medicine and healthcare | 1445 | 1366 | R1 0528 |
| LMArena Text: legal and government | 1419 | 1396 | R1 0528 |
| LMArena Text: business and finance | 1402 | 1380 | R1 0528 |
| FACTS Benchmark Suite | Not measured | 72.5% | Only GPT-6 Sol measured |
| PRBench Finance | 32.7% | Not measured | Only R1 0528 measured |
| PRBench Legal | 36.6% | 38.6% | GPT-6 Sol |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | 1293 | GPT-6 Sol |
| Design Arena: UI components | 1100 | 1291 | GPT-6 Sol |
| Design Arena: game dev | 1097 | 1311 | GPT-6 Sol |
| Design Arena: data viz | 1182 | 1271 | GPT-6 Sol |
| Design Arena: 3D | 1110 | 1314 | GPT-6 Sol |
| Design Arena: all code categories | 1138 | 1300 | GPT-6 Sol |
| Design Arena: SVG | 1038 | 1313 | GPT-6 Sol |
| Design Arena: ASCII art | Not measured | 1222 | Only GPT-6 Sol measured |
| LiveBench design | Not measured | 82.2% | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index144
| Benchmark | R1 0528 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.2% | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 56.6% | Only GPT-6 Sol measured |
| SAGE (Vals AI) | Not measured | 44.8% | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | Not measured | 82.0% | Only GPT-6 Sol measured |
| IFBench | 39.6% | Not measured | Only R1 0528 measured |
| Long context reasoning (AA-LCR) | 55.7% | 83.7% | GPT-6 Sol |
| DTBench | Not measured | 97.3% | Only GPT-6 Sol measured |
| LMCA | Not measured | 59.1% | Only GPT-6 Sol measured |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | Not measured | Only R1 0528 measured |
| Furniture assembly | Not measured | 58.3% | Only GPT-6 Sol measured |
| LMArena Text | 1428 | 1398 | R1 0528 |
| LMArena Text: instruction following | 1382 | 1413 | GPT-6 Sol |
| LMArena Text: creative writing | 1405 | 1378 | R1 0528 |
| LMArena Vision | Not measured | 1240 | Only GPT-6 Sol measured |
| LMArena Text: English | 1437 | 1396 | R1 0528 |
| LMArena Text: non-English | 1412 | 1388 | R1 0528 |
| LMArena Text: Chinese | 1442 | 1412 | R1 0528 |
| LMArena Text: German | 1404 | 1379 | R1 0528 |
| LMArena Text: Japanese | 1391 | 1377 | R1 0528 |
| LMArena Text: Korean | 1360 | 1336 | R1 0528 |
| LMArena Text: French | 1417 | 1399 | R1 0528 |
| LMArena Text: Spanish | 1411 | 1387 | R1 0528 |
| LMArena Text: Russian | 1423 | 1402 | R1 0528 |
| LMArena Text: Polish | 1428 | 1372 | R1 0528 |
| LMArena Text: multi-turn | 1405 | 1414 | GPT-6 Sol |
| LMArena Text: longer queries | 1391 | 1416 | GPT-6 Sol |
| LMArena Text: writing and language | 1402 | 1389 | R1 0528 |
| LMArena Text: entertainment and media | 1400 | 1373 | R1 0528 |
| LMArena Vision: English | Not measured | 1229 | Only GPT-6 Sol measured |
| LMArena Vision: reading text | Not measured | 1258 | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | Not measured | 1219 | Only GPT-6 Sol measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | R1 0528 | GPT-6 Sol | 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
R1 0528 costs less
Repository review
50K input + 3K output tokens
R1 0528 costs less
Agent loop
200K input + 10K output tokens
R1 0528 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 | DeepSeek R1 0528 | OpenAI GPT-6 Sol |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | May 28, 2025 | September 22, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.50 | $2.00 |
| Output $/Mtok | $2.18 | $10.00 |
| Coding index | Not benchmarked | 76.0 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is R1 0528 better than GPT-6 Sol for coding?
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding. Pick R1 0528 for output tokens 4.6x cheaper ($2.18 vs $10.00 per million) and work measured by LMArena Text: software and IT or LMArena Text: hard prompts in English, where it leads.
Which is cheaper, R1 0528 or GPT-6 Sol?
R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; GPT-6 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, R1 0528 or GPT-6 Sol?
GPT-6 Sol, with 1.05M tokens against 164K.
How many benchmarks is the R1 0528 vs GPT-6 Sol comparison based on?
45 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and GPT-6 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.