Ember-1 vs Mercury 2.5
Ember-1 leads Mercury 2.5 on coding, 52.6 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 100.0x less per output token ($0.15 vs $15.00 per million). Updated October 22, 2026; 11 benchmarks have a result for both.
Ember-1 or Mercury 2.5: which to pick
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 100.0x cheaper ($0.15 vs $15.00 per million).
- Shared results
- 11
- Ember-1 only
- 3
- Mercury 2.5 only
- 11
- Like-for-like categories
- 3 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 1.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Mercury 2.5 has a AA Intelligence Index result, 12.3.
Directional only
Long documents
Listed context window
Ember-1
Ember-1 takes 1.05M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Ember-1 $0.011, Mercury 2.5 $0.0001 per turn.
List prices
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- Coding, 40.7 points apart on average over 5 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ember-1 83.9% against Mercury 2.5 3.7%, 80.2 points apart on a 0 to 100 scale.
- Output price
- Ember-1 $15.00 against Mercury 2.5 $0.15 per million output tokens, 100.0x apart.
- Context window
- Ember-1 takes 1.05M tokens, Mercury 2.5 260K.
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 | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Agentic work | 5 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | 20.7% | 0.0% | Ember-1 |
| Vibe Code Bench (Vals AI) | 83.9% | 3.7% | Ember-1 |
| Code migration (Vals AI) | 32.5% | 4.5% | Ember-1 |
| IOI (Vals AI) | 46.3% | 2.4% | Ember-1 |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 34.5% | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | Not measured | 18.1% | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 69.5% | 45.5% | Ember-1 |
| SciCode | Not measured | 38.5% | Only Mercury 2.5 measured |
| ALE-Bench | Not measured | 301.6 | Only Mercury 2.5 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.3 | Only Mercury 2.5 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | 51.8% | 18.9% | Ember-1 |
| Tax Agent Bench (Vals AI) | 31.1% | 2.5% | Ember-1 |
| Legal Research Bench (Vals AI) | 44.7% | 4.3% | Ember-1 |
| Excel Modeling Benchmark (Vals AI) | 63.4% | 8.8% | Ember-1 |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Ember-1 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | 0.0% | Ember-1 |
| Vals Science Index | 31.8% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 11.8% | Only Mercury 2.5 measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| ProofBench | Not measured | 3.0% | Only Mercury 2.5 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 83.1% | Only Mercury 2.5 measured |
| MedCode (Vals AI) | Not measured | 31.3% | Only Mercury 2.5 measured |
| Neither model has a result on the other 16 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ember-1 | Mercury 2.5 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | 45.3% | Ember-1 |
| MedScribe (Vals AI) | Not measured | 55.1% | Only Mercury 2.5 measured |
| Long context reasoning (AA-LCR) | Not measured | 71.7% | Only Mercury 2.5 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 | Mercury 2.5 | 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
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 |
|---|---|---|
| Maker | Fireworks | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | September 8, 2026 |
| Context window | 1.05M | 260K |
| Input $/Mtok | $3.00 | $0.04 |
| Output $/Mtok | $15.00 | $0.15 |
| Coding index | 52.6 | 1.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than Mercury 2.5 for coding?
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 100.0x cheaper ($0.15 vs $15.00 per million).
Which is cheaper, Ember-1 or Mercury 2.5?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Mercury 2.5 costs $0.04 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Ember-1 or Mercury 2.5?
Ember-1, with 1.05M tokens against 260K.
How many benchmarks is the Ember-1 vs Mercury 2.5 comparison based on?
11 benchmarks have a result for both models as of October 22, 2026. Ember-1's coding index rests on 2 independent benchmarks and Mercury 2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.