GPT-5.2-Codex vs Reka Flash 3
GPT-5.2-Codex leads Reka Flash 3 on the Artificial Analysis Intelligence Index, 28.5 to 6.4, and Reka Flash 3 costs 70.0x less per output token ($0.20 vs $14.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
GPT-5.2-Codex or Reka Flash 3: which to pick
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Reka Flash 3 has none, so the two cannot be ranked on coding.
Pick Reka Flash 3 for output tokens 70.0x cheaper ($0.20 vs $14.00 per million).
- Shared results
- 7
- GPT-5.2-Codex only
- 15
- Reka Flash 3 only
- 5
- Like-for-like categories
- 5 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-5.2-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.2-Codex
GPT-5.2-Codex leads, 28.5 against 6.4.
Same board, both measured
Long documents
Listed context window
GPT-5.2-Codex
GPT-5.2-Codex takes 400K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Reka Flash 3
GPT-5.2-Codex $0.0088, Reka Flash 3 $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2-Codex has the number, $0.43.
Directional only
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, Reka Flash 3 not benchmarked.
- Widest category
- Agentic work, 92.1 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GPT-5.2-Codex 92.1% against Reka Flash 3 0.0%, 92.1 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against Reka Flash 3 $0.20 per million output tokens, 70.0x apart.
- Context window
- GPT-5.2-Codex takes 400K 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-5.2-Codex | Bars | Reka Flash 3 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | 66.3% | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev | 1339 | Not measured | Only GPT-5.2-Codex measured |
| LiveCodeBench (Vals AI) | 88.0% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Verified (Vals AI) | 72.4% | Not measured | Only GPT-5.2-Codex measured |
| Vibe Code Bench (Vals AI) | 37.9% | Not measured | Only GPT-5.2-Codex measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 43.5% | Only Reka Flash 3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | 0.0% | GPT-5.2-Codex |
| Terminal-Bench | 66.5% | Not measured | Only GPT-5.2-Codex measured |
| ALE-Bench | 1299.9 | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev: React | 1329 | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev: HTML | 1348 | Not measured | Only GPT-5.2-Codex measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.5 | 6.4 | GPT-5.2-Codex |
| 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-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1051 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building full-stack apps | 993 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building mobile apps | 1090 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Android apps | 1176 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Godot games | 1142 | Not measured | Only GPT-5.2-Codex measured |
| τ²-Bench Telecom | 92.1% | 0.0% | GPT-5.2-Codex |
| BALROG | Not measured | 29.2% | Only Reka Flash 3 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.9% | 52.9% | GPT-5.2-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 4.4% | GPT-5.2-Codex |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 33.7 | Only Reka Flash 3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 33.7% | Only Reka Flash 3 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 66.9% | Only Reka Flash 3 measured |
| Neither model has a result on the other 17 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2-Codex | Reka Flash 3 | Leader |
|---|---|---|---|
| IFBench | 77.6% | 30.4% | GPT-5.2-Codex |
| Long context reasoning (AA-LCR) | 82.3% | 0.0% | GPT-5.2-Codex |
| 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-5.2-Codex | 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-5.2-Codex | Reka Flash 3 |
|---|---|---|
| Maker | OpenAI | Reka |
| Weights | No public weights listed | Open weights |
| Released | January 14, 2026 | March 12, 2025 |
| Context window | 400K | 66K |
| Input $/Mtok | $1.75 | $0.10 |
| Output $/Mtok | $14.00 | $0.20 |
| Coding index | 45.4 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $0.43 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than Reka Flash 3 for coding?
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Reka Flash 3 has none, so the two cannot be ranked on coding. Pick Reka Flash 3 for output tokens 70.0x cheaper ($0.20 vs $14.00 per million).
Which is cheaper, GPT-5.2-Codex or Reka Flash 3?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Reka Flash 3 costs $0.10 and $0.20. Cost per solved task is known for GPT-5.2-Codex only.
Which has the bigger context window, GPT-5.2-Codex or Reka Flash 3?
GPT-5.2-Codex, with 400K tokens against 66K.
How many benchmarks is the GPT-5.2-Codex vs Reka Flash 3 comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. GPT-5.2-Codex's coding index rests on 3 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.