R1 0528 vs GPT-4o-mini (2024-07-18)
Updated October 21, 2026. 35 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 3.6 for GPT-4o-mini (2024-07-18).
Pick GPT-4o-mini (2024-07-18) when output tokens cost 3.6x less.
- Shared results
- 35
- R1 0528 only
- 24
- GPT-4o-mini (2024-07-18) only
- 11
- Like-for-like categories
- 5 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
R1 0528
R1 0528 scores 71.4 against 3.6.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only R1 0528 has a AA Intelligence Index result, 13.1.
Directional only
Web design
Design Arena: websites
No call
Only R1 0528 has a Design Arena: websites result, 1149.
Directional only
Long documents
Listed context window
R1 0528
R1 0528 takes 164K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini (2024-07-18)
R1 0528 $0.0016, GPT-4o-mini (2024-07-18) $0.0004 per turn.
List prices
At a glance
- Coding index
- R1 0528 71.4 from 1 benchmark, GPT-4o-mini (2024-07-18) 3.6 from 1 benchmark.
- Widest category
- Math, 37.4 points apart on average over 4 shared benchmarks.
- Widest single gap
- Aider polyglot: R1 0528 71.4% against GPT-4o-mini (2024-07-18) 3.6%, 67.8 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.15 against GPT-4o-mini (2024-07-18) $0.60 per million output tokens, 3.6x apart.
- Context window
- R1 0528 takes 164K tokens, GPT-4o-mini (2024-07-18) 128K.
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-4o-mini (2024-07-18) | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 35 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index40
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | 3.6% | R1 0528 |
| LiveCodeBench (Artificial Analysis run) | 77.0% | Not measured | Only R1 0528 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only R1 0528 measured |
| WeirdML | 41.6% | 11.8% | R1 0528 |
| ALE-Bench | 804.1 | Not measured | Only R1 0528 measured |
| LMArena Text: coding | 1427 | 1290 | R1 0528 |
| LMArena Text: software and IT | 1435 | 1291 | R1 0528 |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 36.5% | Not measured | Only R1 0528 measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| BALROG | Not measured | 17.4% | Only GPT-4o-mini (2024-07-18) measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | Not measured | Only R1 0528 measured |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | Not measured | Only R1 0528 measured |
| GPQA Diamond (Epoch AI run) | 76.3% | 37.7% | R1 0528 |
| ARC-AGI | 21.2% | Not measured | Only R1 0528 measured |
| ARC-AGI-2 | 1.1% | Not measured | Only R1 0528 measured |
| SimpleBench | 40.8% | 10.7% | R1 0528 |
| Chess puzzles | Not measured | 3.0% | Only GPT-4o-mini (2024-07-18) measured |
| Mystery game puzzles | Not measured | 12.0% | Only GPT-4o-mini (2024-07-18) measured |
| VPCT | Not measured | 34.0% | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts | 1415 | 1267 | R1 0528 |
| LMArena Text: expert | 1394 | 1234 | R1 0528 |
| LMArena Text: hard prompts in English | 1422 | 1278 | R1 0528 |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | 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% | 6.9% | R1 0528 |
| FrontierMath, tiers 1 to 3 | Not measured | 0.7% | Only GPT-4o-mini (2024-07-18) measured |
| MATH level 5 | 96.6% | 52.6% | R1 0528 |
| LMArena Text: math | 1400 | 1267 | R1 0528 |
| LMArena Text: mathematical work | 1415 | 1271 | R1 0528 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| SimpleQA Verified | Not measured | 8.3% | Only GPT-4o-mini (2024-07-18) measured |
| MMLU | Not measured | 76.7% | Only GPT-4o-mini (2024-07-18) measured |
| GeoBench | Not measured | 64.0% | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: science | 1430 | 1286 | R1 0528 |
| LMArena Text: medicine and healthcare | 1445 | 1282 | R1 0528 |
| LMArena Text: legal and government | 1419 | 1305 | R1 0528 |
| LMArena Text: business and finance | 1402 | 1265 | R1 0528 |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | Not measured | Only R1 0528 measured |
| Design Arena: UI components | 1102 | Not measured | Only R1 0528 measured |
| Design Arena: game dev | 1098 | Not measured | Only R1 0528 measured |
| Design Arena: data viz | 1182 | Not measured | Only R1 0528 measured |
| Design Arena: 3D | 1111 | Not measured | Only R1 0528 measured |
| Design Arena: all code categories | 1139 | Not measured | Only R1 0528 measured |
| Design Arena: SVG | 1038 | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| IFBench | 39.6% | Not measured | Only R1 0528 measured |
| Long context reasoning (AA-LCR) | 55.7% | Not measured | Only R1 0528 measured |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | 67.2% | R1 0528 |
| LMArena Text | 1428 | 1286 | R1 0528 |
| LMArena Text: instruction following | 1382 | 1258 | R1 0528 |
| LMArena Text: creative writing | 1405 | 1268 | R1 0528 |
| LMArena Vision | Not measured | 1066 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: English | 1437 | 1301 | R1 0528 |
| LMArena Text: non-English | 1412 | 1266 | R1 0528 |
| LMArena Text: Chinese | 1442 | 1265 | R1 0528 |
| LMArena Text: German | 1404 | 1272 | R1 0528 |
| LMArena Text: Japanese | 1391 | 1216 | R1 0528 |
| LMArena Text: Korean | 1360 | 1195 | R1 0528 |
| LMArena Text: French | 1417 | 1297 | R1 0528 |
| LMArena Text: Spanish | 1411 | 1276 | R1 0528 |
| LMArena Text: Russian | 1423 | 1275 | R1 0528 |
| LMArena Text: Polish | 1428 | 1244 | R1 0528 |
| LMArena Text: multi-turn | 1405 | 1285 | R1 0528 |
| LMArena Text: longer queries | 1391 | 1289 | R1 0528 |
| LMArena Text: writing and language | 1402 | 1282 | R1 0528 |
| LMArena Text: entertainment and media | 1400 | 1253 | R1 0528 |
| LMArena Vision: English | Not measured | 1072 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: Chinese | Not measured | 1033 | Only GPT-4o-mini (2024-07-18) 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
| Benchmark | R1 0528 | GPT-4o-mini (2024-07-18) | 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-4o-mini (2024-07-18) costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini (2024-07-18) costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini (2024-07-18) 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-4o-mini (2024-07-18) |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | May 28, 2025 | July 18, 2024 |
| Context window | 164K | 128K |
| Input $/Mtok | $0.50 | $0.15 |
| Output $/Mtok | $2.15 | $0.60 |
| Coding index | 71.4 | 3.6 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is R1 0528 better than GPT-4o-mini (2024-07-18) for coding?
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 3.6 for GPT-4o-mini (2024-07-18). Pick GPT-4o-mini (2024-07-18) when output tokens cost 3.6x less.
Which is cheaper, R1 0528 or GPT-4o-mini (2024-07-18)?
R1 0528 costs $0.50 per million input tokens and $2.15 per million output tokens; GPT-4o-mini (2024-07-18) costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, R1 0528 or GPT-4o-mini (2024-07-18)?
R1 0528, with 164K tokens against 128K.
How many benchmarks is the R1 0528 vs GPT-4o-mini (2024-07-18) comparison based on?
35 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 1 independent benchmark and GPT-4o-mini (2024-07-18)'s on 1. Where only one model has a result, the page says so instead of naming a winner.