Ember-1 vs GPT-4o-mini (2024-07-18)
GPT-4o-mini (2024-07-18) costs 25.0x less per output token than Ember-1 ($0.60 vs $15.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 52.6
- Overall
- No data
- Output $/M
- $15.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
Ember-1 or GPT-4o-mini (2024-07-18): which to pick
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; GPT-4o-mini (2024-07-18) has none, so the two cannot be ranked on coding.
Pick GPT-4o-mini (2024-07-18) for output tokens 25.0x cheaper ($0.60 vs $15.00 per million).
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); GPT-4o-mini (2024-07-18) on Aider polyglot, WeirdML and LMArena Text: coding. Compare them on price and context instead.
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 Ember-1 has a coding score, so no call is made.
One side not measured
Long documents
Listed context window
Ember-1
Ember-1 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini (2024-07-18)
Ember-1 $0.011, GPT-4o-mini (2024-07-18) $0.0004 per turn.
List prices
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, GPT-4o-mini (2024-07-18) not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Ember-1 $15.00 against GPT-4o-mini (2024-07-18) $0.60 per million output tokens, 25.0x apart.
- Context window
- Ember-1 takes 1.05M tokens, GPT-4o-mini (2024-07-18) 128K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 3.6% | Only GPT-4o-mini (2024-07-18) measured |
| Terminal-Bench 4 (Vals AI) | 20.7% | Not measured | Only Ember-1 measured |
| Vibe Code Bench (Vals AI) | 83.9% | Not measured | Only Ember-1 measured |
| 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 |
| WeirdML | Not measured | 11.8% | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: coding | Not measured | 1290 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: software and IT | Not measured | 1291 | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 34 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| 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 |
| BALROG | Not measured | 17.4% | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 37.7% | Only GPT-4o-mini (2024-07-18) measured |
| SimpleBench | Not measured | 10.7% | Only GPT-4o-mini (2024-07-18) measured |
| 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 | Not measured | 1267 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: expert | Not measured | 1234 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts in English | Not measured | 1278 | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 6.9% | Only GPT-4o-mini (2024-07-18) measured |
| FrontierMath, tiers 1 to 3 | Not measured | 0.7% | Only GPT-4o-mini (2024-07-18) measured |
| MATH level 5 | Not measured | 52.6% | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: math | Not measured | 1267 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: mathematical work | Not measured | 1271 | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| 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 | Not measured | 1286 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: medicine and healthcare | Not measured | 1282 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: legal and government | Not measured | 1305 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: business and finance | Not measured | 1265 | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 13 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards measured
| Benchmark | Ember-1 | GPT-4o-mini (2024-07-18) | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| Creative writing (Lech Mazur) | Not measured | 67.2% | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text | Not measured | 1286 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: instruction following | Not measured | 1258 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: creative writing | Not measured | 1268 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision | Not measured | 1066 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: English | Not measured | 1301 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: non-English | Not measured | 1266 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Chinese | Not measured | 1265 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: German | Not measured | 1272 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Japanese | Not measured | 1216 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Korean | Not measured | 1195 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: French | Not measured | 1297 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Spanish | Not measured | 1276 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Russian | Not measured | 1275 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Polish | Not measured | 1244 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: multi-turn | Not measured | 1285 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: longer queries | Not measured | 1289 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: writing and language | Not measured | 1282 | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: entertainment and media | Not measured | 1253 | Only GPT-4o-mini (2024-07-18) measured |
| 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 26 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 | Fireworks Ember-1 | OpenAI GPT-4o-mini (2024-07-18) |
|---|---|---|
| Maker | Fireworks | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | July 18, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $3.00 | $0.15 |
| Output $/Mtok | $15.00 | $0.60 |
| Coding index | 52.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than GPT-4o-mini (2024-07-18) for coding?
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; GPT-4o-mini (2024-07-18) has none, so the two cannot be ranked on coding. Pick GPT-4o-mini (2024-07-18) for output tokens 25.0x cheaper ($0.60 vs $15.00 per million).
Which is cheaper, Ember-1 or GPT-4o-mini (2024-07-18)?
Ember-1 costs $3.00 per million input tokens and $15.00 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, Ember-1 or GPT-4o-mini (2024-07-18)?
Ember-1, with 1.05M tokens against 128K.
Has any benchmark tested both Ember-1 and GPT-4o-mini (2024-07-18)?
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); GPT-4o-mini (2024-07-18) on Aider polyglot, WeirdML and LMArena Text: coding. Compare them on price and context instead. Data as of October 22, 2026.