Ember-1 vs GPT-5.1-Codex
Ember-1 leads GPT-5.1-Codex on coding, 52.6 to 15.3 on the Vibe Coding Index, and GPT-5.1-Codex costs 1.5x less per output token ($10.00 vs $15.00 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
Ember-1 or GPT-5.1-Codex: which to pick
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex.
Pick GPT-5.1-Codex for output tokens 1.5x cheaper ($10.00 vs $15.00 per million).
- Shared results
- 1
- Ember-1 only
- 13
- GPT-5.1-Codex only
- 25
- Like-for-like categories
- 1 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
Ember-1
Ember-1 scores 52.6 against 15.3.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only GPT-5.1-Codex has a AA Intelligence Index result, 23.7.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.1-Codex has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
Ember-1
Ember-1 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.1-Codex
Ember-1 $0.011, GPT-5.1-Codex $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, GPT-5.1-Codex 15.3 from 2 benchmarks.
- Widest category
- Coding, 70.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): Ember-1 83.9% against GPT-5.1-Codex 13.1%, 70.8 points apart on a 0 to 100 scale.
- Output price
- Ember-1 $15.00 against GPT-5.1-Codex $10.00 per million output tokens, 1.5x apart.
- Context window
- Ember-1 takes 1.05M tokens, GPT-5.1-Codex 400K.
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 | Ember-1 | Bars | GPT-5.1-Codex | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 66.0% | Only GPT-5.1-Codex measured |
| LMArena WebDev | Not measured | 1337 | Only GPT-5.1-Codex measured |
| LiveCodeBench (Vals AI) | Not measured | 85.5% | Only GPT-5.1-Codex measured |
| Terminal-Bench 4 (Vals AI) | 20.7% | Not measured | Only Ember-1 measured |
| Vibe Code Bench (Vals AI) | 83.9% | 13.1% | Ember-1 |
| Code migration (Vals AI) | 32.5% | Not measured | Only Ember-1 measured |
| IOI (Vals AI) | 46.3% | Not measured | Only Ember-1 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Ember-1 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 84.9% | Only GPT-5.1-Codex measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only GPT-5.1-Codex measured |
| Terminal-Bench | Not measured | 57.8% | Only GPT-5.1-Codex measured |
| ALE-Bench | Not measured | 1244.9 | Only GPT-5.1-Codex measured |
| LMArena WebDev: HTML | Not measured | 1346 | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 23.7 | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1018 | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 1086 | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1191 | Only GPT-5.1-Codex measured |
| Finance Agent (Vals AI) | 51.8% | Not measured | Only Ember-1 measured |
| Tax Agent Bench (Vals AI) | 31.1% | Not measured | Only Ember-1 measured |
| Legal Research Bench (Vals AI) | 44.7% | Not measured | Only Ember-1 measured |
| Excel Modeling Benchmark (Vals AI) | 63.4% | Not measured | Only Ember-1 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Ember-1 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Ember-1 measured |
| Vals Science Index | 31.8% | Not measured | Only Ember-1 measured |
| τ²-Bench Telecom | Not measured | 83.0% | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 86.0% | Only GPT-5.1-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 25.7% | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 95.7 | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 95.7% | Only GPT-5.1-Codex 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 | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 86.0% | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1162 | Only GPT-5.1-Codex measured |
| Design Arena: UI components | Not measured | 1237 | Only GPT-5.1-Codex measured |
| Design Arena: game dev | Not measured | 1138 | Only GPT-5.1-Codex measured |
| Design Arena: data viz | Not measured | 1213 | Only GPT-5.1-Codex measured |
| Design Arena: all code categories | Not measured | 1152 | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| IFBench | Not measured | 70.0% | Only GPT-5.1-Codex measured |
| Long context reasoning (AA-LCR) | Not measured | 69.3% | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | GPT-5.1-Codex | 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-5.1-Codex costs less
Repository review
50K input + 3K output tokens
GPT-5.1-Codex costs less
Agent loop
200K input + 10K output tokens
GPT-5.1-Codex 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 | Fireworks Ember-1 | OpenAI GPT-5.1-Codex |
|---|---|---|
| Maker | Fireworks | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | November 13, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $3.00 | $1.25 |
| Output $/Mtok | $15.00 | $10.00 |
| Coding index | 52.6 | 15.3 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $0.892 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than GPT-5.1-Codex for coding?
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex. Pick GPT-5.1-Codex for output tokens 1.5x cheaper ($10.00 vs $15.00 per million).
Which is cheaper, Ember-1 or GPT-5.1-Codex?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; GPT-5.1-Codex costs $1.25 and $10.00. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, Ember-1 or GPT-5.1-Codex?
Ember-1, with 1.05M tokens against 400K.
How many benchmarks is the Ember-1 vs GPT-5.1-Codex comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. Ember-1's coding index rests on 2 independent benchmarks and GPT-5.1-Codex's on 2. Where only one model has a result, the page says so instead of naming a winner.