Ember-1 vs Gemini 3.7 Flash

Updated September 28, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Ember-1

Fireworks

—

Evidence status unavailable

90% interval unavailable

Model B

Gemini 3.7 Flash

Google

67.53/100

Supported · Public rank #20

90% interval 62.7–72.3

Shared results: 3
Ember-1 only: 2
Gemini 3.7 Flash only: 22
Like-for-like categories: 0 / 8

Supported: Gemini 3.7 FlashHow the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Long documents
Prompts that approach the documented context limit
Ember-1
Ember-1 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Ember-1 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ember-1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—Ember-159.4Gemini 3.7 Flash

Not comparable · BenchAlign v5.7

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: 57.9; Supported · #21/111
Basis: BenchAlign v5.7 lane · 2 vs 7 public rows
Reading: Not comparable

Coding

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: 59.4; Supported · #18/136
Basis: BenchAlign v5.7 lane · 3 vs 6 public rows
Reading: Not comparable

Reasoning

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: 77.9; Unranked · 5 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: 83.6; #10/50
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: 71.0; Supported · #11/160
Basis: BenchAlign v5.7 lane · 0 vs 6 public rows
Reading: Not comparable

Multilingual

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Ember-1: Not ranked
Gemini 3.7 Flash: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Ember-1 and Gemini 3.7 Flash
Category	Ember-1	Gemini 3.7 Flash	Basis	Reading
Agentic	Not ranked	57.9Supported · #21/111	Not comparableBenchAlign v5.7 lane · 2 vs 7 public rows	Not comparable
Coding	Not ranked	59.4Supported · #18/136	Not comparableBenchAlign v5.7 lane · 3 vs 6 public rows	Not comparable
Reasoning	Not ranked	77.9Unranked · 5 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	Not ranked	83.6#10/50	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Knowledge	Not ranked	71.0Supported · #11/160	Not comparableBenchAlign v5.7 lane · 0 vs 6 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Ember-1: $0.0105; Fits in one request
Gemini 3.7 Flash: $0.00262; Fits in one request

Gemini 3.7 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Ember-1: $0.195; Fits in one request
Gemini 3.7 Flash: $0.04875; Fits in one request

Gemini 3.7 Flash has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Ember-1: $0.27; Fits in one request
Gemini 3.7 Flash: $0.0675; Fits in one request

Gemini 3.7 Flash has the lower modeled cost

Costs use the listed standard API rates.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationEmber-1Gemini 3.7 Flash

Context window

Maximum documented context; output-token limits may be lower.

Ember-1

1.04M

Fireworks Ember-1 model page

Gemini 3.7 Flash

Google Gemini 3.7 Flash API documentation

API model ID

Ember-1

accounts/fireworks/models/ember-1

Fireworks Ember-1 model page

Gemini 3.7 Flash

gemini-3.7-flash

Google Gemini 3.7 Flash API documentation

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Ember-1

$0.3 per 1M cached input tokens

Fireworks Ember-1 model page

Gemini 3.7 Flash

$0.075 per 1M cached input tokens

Google Gemini API pricing

Documented inputs

Ember-1

Not sourced

Gemini 3.7 Flash

text, image, video, audio, pdf

Google Gemini 3.7 Flash API documentation

Documented outputs

Ember-1

Not sourced

Gemini 3.7 Flash

text

Google Gemini 3.7 Flash API documentation

Provider availability

Ember-1

Not sourced

Gemini 3.7 Flash

Generally Available · Gemini API, Google AI Studio, Gemini App - Spark, Gemini Enterprise App, Gemini Enterprise Agent Platform, Google Antigravity

Google DeepMind Gemini 3.7 Flash model card

Reasoning profile

Ember-1

Reasoning

Gemini 3.7 Flash

Reasoning

Weight access

Ember-1

Proprietary

Gemini 3.7 Flash

Proprietary

License

Ember-1

Proprietary

Gemini 3.7 Flash

Proprietary

Release date

Ember-1

2026-09-23

Gemini 3.7 Flash

2026-08-13

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: Repository review: $0.195 vs $0.04875. Cache-heavy agent loop: $0.27 vs $0.0675.
Context tradeoff: Ember-1 has the larger documented window (1.04M).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Ember-1 or Gemini 3.7 Flash?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Ember-1 or Gemini 3.7 Flash?

Ember-1 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Ember-1 or Gemini 3.7 Flash?

Ember-1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Ember-1 or Gemini 3.7 Flash?

For the stated presets, chat costs $0.0105 on Ember-1 and $0.00263 on Gemini 3.7 Flash; repository review costs $0.195 and $0.04875; the cache-heavy agent loop costs $0.27 and $0.0675. Costs use the listed standard API rates.

Which has the larger context window, Ember-1 or Gemini 3.7 Flash?

Ember-1 has the larger documented context window: 1.04M, compared with 1M.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence27 rows

Agentic

Terminal-Bench 2.1
Ember-182.0%
Source
Gemini 3.7 Flash85.8%
Source
Gemini 3.7 Flash leads this result
τ²-bench Airline
Ember-166.0%
Source
Gemini 3.7 Flash—
Not directly comparable
Terminal-Bench 3.0
Ember-1—
Gemini 3.7 Flash14.9%
Source
Not directly comparable
AutomationBench
Ember-1—
Gemini 3.7 Flash30.4%
Source
Not directly comparable
OSWorld 2.0
Ember-1—
Gemini 3.7 Flash47.9%
Source
Not directly comparable
Agents' Last Exam
Ember-1—
Gemini 3.7 Flash26.3%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Ember-1—
Gemini 3.7 Flash77.5%
Source
Not directly comparable
ApprenticeBench
Ember-1—
Gemini 3.7 Flash16%
Source
Not directly comparable

Coding

Terminal-Bench 2.1
Ember-182.0%
Source
Gemini 3.7 Flash85.8%
Source
Gemini 3.7 Flash leads this result
SWE-bench Verified
Ember-192.2%
Source
Gemini 3.7 Flash—
Not directly comparable
DeepSWE
Ember-175.2%
Source
Gemini 3.7 Flash65.3%
Source
Ember-1 leads this result
FrontierCode 1.1 Main
Ember-1—
Gemini 3.7 Flash43.6%
Source
Not directly comparable
FrontierSWE v2
Ember-1—
Gemini 3.7 Flash20.3%
Source
Not directly comparable
LiveCodeBench (Vals)
Ember-1—
Gemini 3.7 Flash88.7%
Source
Not directly comparable
SWE-bench (Vals)
Ember-1—
Gemini 3.7 Flash80.8%
Source
Not directly comparable

Reasoning

MRCR v2 64K-128K
Ember-1—
Gemini 3.7 Flash97%
Source
Not directly comparable
ARC-AGI-1
Ember-1—
Gemini 3.7 Flash95.50%
Source
Not directly comparable
ARC-AGI-2
Ember-1—
Gemini 3.7 Flash84.6%
Source
Not directly comparable

Multimodal

CharXiv w/o tools
Ember-1—
Gemini 3.7 Flash84.5%
Source
Not directly comparable
CharXiv
Ember-1—
Gemini 3.7 Flash88.7%
Source
Not directly comparable
LVBench
Ember-1—
Gemini 3.7 Flash85.4%
Source
Not directly comparable

Knowledge

HLE-Verified
Ember-1—
Gemini 3.7 Flash53.6%
Source
Not directly comparable
LABBench2
Ember-1—
Gemini 3.7 Flash82.1%
Source
Not directly comparable
BioMysteryBench (human-solvable)
Ember-1—
Gemini 3.7 Flash87.1%
Source
Not directly comparable
BioMysteryBench (human-difficult)
Ember-1—
Gemini 3.7 Flash43.5%
Source
Not directly comparable
GPQA Diamond (Vals)
Ember-1—
Gemini 3.7 Flash93.9%
Source
Not directly comparable
MMLU-Pro (Vals)
Ember-1—
Gemini 3.7 Flash90.1%
Source
Not directly comparable

27 public results · 3 shared

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Last updated September 28, 2026

Ember-1 vs Gemini 3.7 Flash

Decision reading

Which one for your work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Ember-1 or Gemini 3.7 Flash?

Which is better for coding, Ember-1 or Gemini 3.7 Flash?

Which is better for agentic tasks, Ember-1 or Gemini 3.7 Flash?

Which costs less, Ember-1 or Gemini 3.7 Flash?

Which has the larger context window, Ember-1 or Gemini 3.7 Flash?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Related comparisons

Watch Ember-1 vs Gemini 3.7 Flash