GPT-4o vs Reka Flash 3
Reka Flash 3 costs 50.0x less per output token than GPT-4o ($0.20 vs $10.00 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
GPT-4o or Reka Flash 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o for a larger context window (128K against 66K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 10
- GPT-4o only
- 18
- Reka Flash 3 only
- 2
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Reka Flash 3 has a AA Intelligence Index result, 6.4.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
GPT-4o
GPT-4o takes 128K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Reka Flash 3
GPT-4o $0.0075, Reka Flash 3 $0.0002 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, Reka Flash 3 not benchmarked.
- Widest category
- Math, 27.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): GPT-4o 49.3% against Reka Flash 3 0.0%, 49.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o $10.00 against Reka Flash 3 $0.20 per million output tokens, 50.0x apart.
- Context window
- GPT-4o takes 128K tokens, Reka Flash 3 66K.
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 | GPT-4o | Bars | Reka Flash 3 | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 1 | 1 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 6 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | Not measured | Only GPT-4o measured |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | 43.5% | Reka Flash 3 |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | 0.0% | GPT-4o |
| SciCode | 1.5% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 6.4 | Only Reka Flash 3 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | 0.0% | GPT-4o |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| BALROG | Not measured | 29.2% | Only Reka Flash 3 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 54.3% | 52.9% | GPT-4o |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | 4.4% | Reka Flash 3 |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 19 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | 33.7 | Reka Flash 3 |
| AIME 2025 (Artificial Analysis run) | 6.0% | 33.7% | Reka Flash 3 |
| MathArena | 3.6% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.8% | 66.9% | GPT-4o |
| MMLU | 88.1% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 883 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 868 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 860 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o | Reka Flash 3 | Leader |
|---|---|---|---|
| IFBench | 34.3% | 30.4% | GPT-4o |
| Long context reasoning (AA-LCR) | 49.3% | 0.0% | GPT-4o |
| DTBench | 64.5% | Not measured | Only GPT-4o measured |
| LMCA | 16.6% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o | Reka Flash 3 | 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
Reka Flash 3 costs less
Repository review
50K input + 3K output tokens
Reka Flash 3 costs less
Agent loop
200K input + 10K output tokens
Reka Flash 3 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-4o | Reka Flash 3 |
|---|---|---|
| Maker | OpenAI | Reka |
| Weights | No public weights listed | Open weights |
| Released | May 13, 2024 | March 12, 2025 |
| Context window | 128K | 66K |
| Input $/Mtok | $2.50 | $0.10 |
| Output $/Mtok | $10.00 | $0.20 |
| 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 GPT-4o better than Reka Flash 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o for a larger context window (128K against 66K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o or Reka Flash 3?
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens; Reka Flash 3 costs $0.10 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o or Reka Flash 3?
GPT-4o, with 128K tokens against 66K.
How many benchmarks is the GPT-4o vs Reka Flash 3 comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. GPT-4o's coding index rests on 0 independent benchmarks and Reka Flash 3's on 0. Where only one model has a result, the page says so instead of naming a winner.