Ember-1 vs Gemini 3.7 Flash
Gemini 3.7 Flash leads Ember-1 on coding, 58.0 to 52.6 on the Vibe Coding Index, and Gemini 3.7 Flash costs 4.0x less per output token ($3.75 vs $15.00 per million). Updated October 21, 2026; 10 benchmarks have a result for both.
vs boards won of 10 shared
Ember-1 or Gemini 3.7 Flash: which to pick
Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 52.6 for Ember-1.
Pick Ember-1 for work measured by Terminal-Bench 4 (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
Model AEmber-1Fireworks52.6/1002 independent benchmarksNo cost per solved taskModel BGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved task
- Shared results
- 10
- Ember-1 only
- 4
- Gemini 3.7 Flash only
- 104
- Like-for-like categories
- 2 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
Gemini 3.7 Flash
Gemini 3.7 Flash scores 58.0 against 52.6.
2 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Gemini 3.7 Flash has a AA Intelligence Index result, 39.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 3.7 Flash has a Design Arena: websites result, 1304.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.7 Flash
Ember-1 $0.011, Gemini 3.7 Flash $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Gemini 3.7 Flash 58.0 from 6 benchmarks.
- Widest category
- Coding, 14.9 points apart on average over 5 shared benchmarks.
- Widest single gap
- CyberBench (Vals AI): Ember-1 69.5% against Gemini 3.7 Flash 43.8%, 25.8 points apart on a 0 to 100 scale.
- Output price
- Ember-1 $15.00 against Gemini 3.7 Flash $3.75 per million output tokens, 4.0x apart.
- Context window
- Both take 1.05M tokens.
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 | Gemini 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 3 | 2 | ||
| Agentic work | 2 | 3 | ||
| All shared boards | 5 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 80.5% | Only Gemini 3.7 Flash measured |
| LMArena WebDev | Not measured | 1591 | Only Gemini 3.7 Flash measured |
| AA Coding Index | Not measured | 71.5 | Only Gemini 3.7 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 88.7% | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 80.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | 20.7% | 12.1% | Ember-1 |
| Vibe Code Bench (Vals AI) | 83.9% | 70.4% | Ember-1 |
| Code migration (Vals AI) | 32.5% | 34.8% | Gemini 3.7 Flash |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | 46.3% | 67.8% | Gemini 3.7 Flash |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | Not measured | 65.9% | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | 69.5% | 43.8% | Ember-1 |
| SciCode | Not measured | 59.8% | Only Gemini 3.7 Flash measured |
| FrontierCode | Not measured | 43.6% | Only Gemini 3.7 Flash measured |
| FrontierSWE | Not measured | 20.3% | Only Gemini 3.7 Flash measured |
| ALE-Bench | Not measured | 904.3 | Only Gemini 3.7 Flash measured |
| LMArena Text: coding | Not measured | 1499 | Only Gemini 3.7 Flash measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: React | Not measured | 1587 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: HTML | Not measured | 1593 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: from an image | Not measured | 1599 | Only Gemini 3.7 Flash measured |
| SciCode | Not measured | 13.8% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.6 | Only Gemini 3.7 Flash measured |
| Epoch Capabilities Index | Not measured | 158.0 | Only Gemini 3.7 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1223 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1208 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1230 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1242 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1264 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | Not measured | 1235 | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | Not measured | 1053 | Only Gemini 3.7 Flash measured |
| LiveBench research | Not measured | 76.5% | Only Gemini 3.7 Flash measured |
| LiveBench browser | Not measured | 56.0% | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | Not measured | 28.3% | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | Not measured | 4.6% | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | 51.8% | 59.0% | Gemini 3.7 Flash |
| Tax Agent Bench (Vals AI) | 31.1% | 22.8% | Ember-1 |
| Legal Research Bench (Vals AI) | 44.7% | 34.6% | Ember-1 |
| Excel Modeling Benchmark (Vals AI) | 63.4% | 71.3% | Gemini 3.7 Flash |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Ember-1 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | 7.1% | Gemini 3.7 Flash |
| Vals Science Index | 31.8% | Not measured | Only Ember-1 measured |
| APEX-Agents | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Remote Labor Index | Not measured | 5.0% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.9% | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | Not measured | 87.8% | Only Gemini 3.7 Flash measured |
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| MMMU Pro (Vals AI) | Not measured | 89.0% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 94.5% | Only Gemini 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 47.9% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Epoch AI run) | Not measured | 94.8% | Only Gemini 3.7 Flash measured |
| ARC-AGI | Not measured | 95.5% | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | Not measured | 84.6% | Only Gemini 3.7 Flash measured |
| Chess puzzles | Not measured | 66.0% | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | Not measured | 37.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: expert | Not measured | 1512 | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Vision: diagrams | Not measured | 1329 | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | Not measured | 1320 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 97.2% | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.6% | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | Not measured | 36.6% | Only Gemini 3.7 Flash measured |
| ProofBench | Not measured | 58.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: math | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: mathematical work | Not measured | 1502 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 90.1% | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | Not measured | 87.3% | Only Gemini 3.7 Flash measured |
| TaxEval (Vals AI) | Not measured | 74.7% | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | Not measured | 66.7% | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | Not measured | 53.4% | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | Not measured | 69.2% | Only Gemini 3.7 Flash measured |
| LMArena Text: science | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1494 | Only Gemini 3.7 Flash measured |
| LMArena Text: legal and government | Not measured | 1496 | Only Gemini 3.7 Flash measured |
| LMArena Text: business and finance | Not measured | 1479 | Only Gemini 3.7 Flash measured |
| FACTS Benchmark Suite | Not measured | 71.2% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1304 | Only Gemini 3.7 Flash measured |
| Design Arena: UI components | Not measured | 1299 | Only Gemini 3.7 Flash measured |
| Design Arena: game dev | Not measured | 1318 | Only Gemini 3.7 Flash measured |
| Design Arena: data viz | Not measured | 1315 | Only Gemini 3.7 Flash measured |
| Design Arena: 3D | Not measured | 1308 | Only Gemini 3.7 Flash measured |
| Design Arena: all code categories | Not measured | 1308 | Only Gemini 3.7 Flash measured |
| Design Arena: SVG | Not measured | 1283 | Only Gemini 3.7 Flash measured |
| Design Arena: ASCII art | Not measured | 1276 | Only Gemini 3.7 Flash measured |
| LiveBench design | Not measured | 73.2% | Only Gemini 3.7 Flash measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 68.0% | Only Gemini 3.7 Flash measured |
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| SAGE (Vals AI) | Not measured | 49.2% | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | Not measured | 83.9% | Only Gemini 3.7 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 83.0% | Only Gemini 3.7 Flash measured |
| DTBench | Not measured | 96.8% | Only Gemini 3.7 Flash measured |
| LMCA | Not measured | 50.4% | Only Gemini 3.7 Flash measured |
| Furniture assembly | Not measured | 26.7% | Only Gemini 3.7 Flash measured |
| LMArena Text | Not measured | 1489 | Only Gemini 3.7 Flash measured |
| LMArena Text: instruction following | Not measured | 1484 | Only Gemini 3.7 Flash measured |
| LMArena Text: creative writing | Not measured | 1488 | Only Gemini 3.7 Flash measured |
| LMArena Vision | Not measured | 1314 | Only Gemini 3.7 Flash measured |
| LMArena Text: English | Not measured | 1483 | Only Gemini 3.7 Flash measured |
| LMArena Text: non-English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Text: Chinese | Not measured | 1552 | Only Gemini 3.7 Flash measured |
| LMArena Text: German | Not measured | 1506 | Only Gemini 3.7 Flash measured |
| LMArena Text: Japanese | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | Not measured | 1481 | Only Gemini 3.7 Flash measured |
| LMArena Text: French | Not measured | 1500 | Only Gemini 3.7 Flash measured |
| LMArena Text: Spanish | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: Russian | Not measured | 1515 | Only Gemini 3.7 Flash measured |
| LMArena Text: Polish | Not measured | 1503 | Only Gemini 3.7 Flash measured |
| LMArena Text: multi-turn | Not measured | 1485 | Only Gemini 3.7 Flash measured |
| LMArena Text: longer queries | Not measured | 1492 | Only Gemini 3.7 Flash measured |
| LMArena Text: writing and language | Not measured | 1491 | Only Gemini 3.7 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1477 | Only Gemini 3.7 Flash measured |
| LMArena Vision: English | Not measured | 1309 | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | Not measured | 1394 | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | Not measured | 1299 | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | Gemini 3.7 Flash | 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
Ember-1$0.011Fits in one request
Gemini 3.7 Flash$0.0026Fits in one request
Gemini 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Ember-1$0.195Fits in one request
Gemini 3.7 Flash$0.049Fits in one request
Gemini 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Ember-1$0.750Fits in one request
Gemini 3.7 Flash$0.188Fits in one request
Gemini 3.7 Flash 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 3.7 Flash |
|---|---|---|
| Maker | Fireworks | |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | August 13, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $3.00 | $0.75 |
| Output $/Mtok | $15.00 | $3.75 |
| Coding index | 52.6 | 58.0 |
| Independent measurements behind it | 2 | 6 |
| Cost per solved task | Not computable | $1.78 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than Gemini 3.7 Flash for coding?
Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 52.6 for Ember-1. Pick Ember-1 for work measured by Terminal-Bench 4 (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, Ember-1 or Gemini 3.7 Flash?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Ember-1 or Gemini 3.7 Flash?
Neither: both take 1.05M tokens.
How many benchmarks is the Ember-1 vs Gemini 3.7 Flash comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. Ember-1's coding index rests on 2 independent benchmarks and Gemini 3.7 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.