Ember-1 vs Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 costs 1.5x less per output token than Ember-1 ($10.00 vs $15.00 per million). Updated October 21, 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
- $10.00
Ember-1 or Gemini 2.5 Pro Preview 06-05: which to pick
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Pro Preview 06-05 for output tokens 1.5x cheaper ($10.00 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); Gemini 2.5 Pro Preview 06-05 on Aider polyglot, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run). 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
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Pro Preview 06-05
Ember-1 $0.011, Gemini 2.5 Pro Preview 06-05 $0.0063 per turn.
List prices
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Gemini 2.5 Pro Preview 06-05 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 Gemini 2.5 Pro Preview 06-05 $10.00 per million output tokens, 1.5x apart.
- Context window
- Both take 1.05M tokens.
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 | Gemini 2.5 Pro Preview 06-05 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 83.1% | Only Gemini 2.5 Pro Preview 06-05 measured |
| LiveCodeBench (Vals AI) | Not measured | 79.2% | Only Gemini 2.5 Pro Preview 06-05 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 77.8% | Only Gemini 2.5 Pro Preview 06-05 measured |
| GSO-Bench | Not measured | 3.9% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 29 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Ember-1 | Gemini 2.5 Pro Preview 06-05 | 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 |
| METR time horizons | Not measured | 55.4% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Remote Labor Index | Not measured | 0.8% | Only Gemini 2.5 Pro Preview 06-05 measured |
| DeepResearch Bench | Not measured | 42.8% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Ember-1 | Gemini 2.5 Pro Preview 06-05 | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 83.6% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 19.9% | Only Gemini 2.5 Pro Preview 06-05 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 84.8% | Only Gemini 2.5 Pro Preview 06-05 measured |
| SimpleBench | Not measured | 62.4% | Only Gemini 2.5 Pro Preview 06-05 measured |
| VPCT | Not measured | 46.4% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 15 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ember-1 | Gemini 2.5 Pro Preview 06-05 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 85.8% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 16 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Ember-1 | Gemini 2.5 Pro Preview 06-05 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| Fiction.LiveBench | Not measured | 91.7% | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 44 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
Gemini 2.5 Pro Preview 06-05 costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro Preview 06-05 costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Pro Preview 06-05 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 | Google Gemini 2.5 Pro Preview 06-05 |
|---|---|---|
| Maker | Fireworks | |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | June 5, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $3.00 | $1.25 |
| Output $/Mtok | $15.00 | $10.00 |
| 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 Gemini 2.5 Pro Preview 06-05 for coding?
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for output tokens 1.5x cheaper ($10.00 vs $15.00 per million).
Which is cheaper, Ember-1 or Gemini 2.5 Pro Preview 06-05?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Gemini 2.5 Pro Preview 06-05 costs $1.25 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Ember-1 or Gemini 2.5 Pro Preview 06-05?
Neither: both take 1.05M tokens.
Has any benchmark tested both Ember-1 and Gemini 2.5 Pro Preview 06-05?
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); Gemini 2.5 Pro Preview 06-05 on Aider polyglot, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.