Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Gemini 3.7 Flash vs LiquidAI: LFM2.5-2.6B (free) benchmark

Name: Gemini 3.7 Flash vs LiquidAI: LFM2.5-2.6B (free) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 3.7 Flash (Google) and LiquidAI: LFM2.5-2.6B (free) (liquid) using the latest snapshots we have as of Aug 17, 2026. LiquidAI: LFM2.5-2.6B (free) wins on output price at $0/1M. Gemini 3.7 Flash has the larger context window (1M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Google

Gemini 3.7 Flash

Google Aug 13 2026 workhorse. Official intro price $0.75/$3.75 per 1M through Dec 31 2026; 1,048,576-token context (Google blog).

Elo 1,530$1.875/1M out

liquid

LiquidAI: LFM2.5-2.6B (free)

Auto-discovered from OpenRouter (liquid/lfm-2.5-2.6b:free). Preview until a second source matches.

$0/1M out

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Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 3.7 Flash (8)vsLiquidAI: LFM2.5-2.6B (free) (2)

Gemini 3.7 Flash: 8W (80%)Overall: Gemini 3.7 FlashLiquidAI: LFM2.5-2.6B (free): 2W (20%)

← Gemini 3.7 FlashLiquidAI: LFM2.5-2.6B (free) →

Gemini 3.7 Flash (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,530vs—

Coding Elo

1,546vs—

SWE-bench

72.4%vs—

LiveBench

69.6%vs—

GPQA Diamond

81.2%vs—

Gemini 3.7 Flash: 5WLiquidAI: LFM2.5-2.6B (free): 0W

Gemini 3.7 Flash (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

215 tok/svs—

Time to first token

82 msvs—

Gemini 3.7 Flash: 2WLiquidAI: LFM2.5-2.6B (free): 0W

LiquidAI: LFM2.5-2.6B (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.88/1Mvs$0/1M

Input price

$0.38/1Mvs$0/1M

Context window

1Mvs128k

Gemini 3.7 Flash: 1WLiquidAI: LFM2.5-2.6B (free): 2W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGemini 3.7 Flash 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

LiquidAI: LFM2.5-2.6B (free)

$1.88/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,530

EloHigh is better

—

Code Elo

High is better

1,546

Code EloHigh is better

—

LiveBench

High is better

69.6%

LiveBenchHigh is better

—

SWE-bench

High is better

72.4%

SWE-benchHigh is better

—

GPQA

High is better

81.2%

GPQAHigh is better

—

TTFT

Low is better

82 ms

TTFTLow is better

—

Speed

High is better

215 tok/s

SpeedHigh is better

—

In $

Low is better

$0.38/1M

In $Low is better

$0/1M

Out $

Low is better

$1.88/1M

Out $Low is better

$0/1M

Context

High is better

+719%1M

ContextHigh is better

128k

Key Selection Recommendations

1
LiquidAI: LFM2.5-2.6B (free):Pick LiquidAI: LFM2.5-2.6B (free) when you are optimizing output cost.
2
Gemini 3.7 Flash:Pick Gemini 3.7 Flash for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatLiquidAI: LFM2.5-2.6B (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 3.7 Flash

Larger window (1M).

Screenshots / visionGemini 3.7 Flash

Gemini 3.7 Flash is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	LiquidAI: LFM2.5-2.6B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 3.7 Flash	Larger window (1M).
Screenshots / vision	Gemini 3.7 Flash	Gemini 3.7 Flash is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

compareAug 13, 2026

Gemini Flash vs Pro: when Flash is the whole product

3.7 Flash vs 3.6 Pro is the current Google volume-versus-upgrade pair.

priceAug 13, 2026

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Jul 21 workhorse that inherited $0.75/$3.75 through year-end. Keep the row; 3.7 is the newer sibling.

launchAug 13, 2026

Gemini 3.7 Flash (Aug 13): $0.75/$3.75 intro through Dec 31 2026

Google’s current workhorse drop. Official intro list and 1,048,576-token context. Compare to Luna and Haiku.

launchJul 15, 2026

Gemini 3.6 Pro: Google’s current Pro-class long-context row

2M context, Pro-class Elo and coding. Upgrade path from Flash is this page, not a vibe check.

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LIVE

Google

Gemini 3.7 Flash

Elo 1,530

LiveBench69.6%

SWE-bench72.4%

Speed215 tok/s

Output cost$1.88/1M

liquid

LiquidAI: LFM2.5-2.6B (free)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0/1M

Frequently Asked Questions

Which is better overall, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: LiquidAI: LFM2.5-2.6B (free) output tokens are $0/1M versus $1.88/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?: We do not have TTFT for both models.
Which has the larger context window?: Gemini 3.7 Flash accepts 1M tokens versus 128k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 3.7 Flash and LiquidAI: LFM2.5-2.6B (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 3.7 Flash matchups →|All LiquidAI: LFM2.5-2.6B (free) matchups →

Gemini 3.7 Flash vs Gemini 3.6 Flash (previous gemini-flash)Gemini 3 Pro vs Gemini 3.7 Flash Gemini 3 Flash vs Gemini 3.7 Flash Gemini 2.0 Flash Thinking vs Gemini 3.7 Flash Gemini 3.6 Pro vs Gemini 3.7 Flash Kimi K3 vs Gemini 3.7 Flash

Gemini 3.7 Flash vs LiquidAI: LFM2.5-2.6B (free) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 3.7 Flash (8)vsLiquidAI: LFM2.5-2.6B (free) (2)

Gemini 3.7 Flash: 8W (80%)Overall: Gemini 3.7 FlashLiquidAI: LFM2.5-2.6B (free): 2W (20%)

← Gemini 3.7 FlashLiquidAI: LFM2.5-2.6B (free) →

Gemini 3.7 Flash (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,530vs—

Coding Elo

1,546vs—

SWE-bench

72.4%vs—

LiveBench

69.6%vs—

GPQA Diamond

81.2%vs—

Gemini 3.7 Flash: 5WLiquidAI: LFM2.5-2.6B (free): 0W

Gemini 3.7 Flash (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

215 tok/svs—

Time to first token

82 msvs—

Gemini 3.7 Flash: 2WLiquidAI: LFM2.5-2.6B (free): 0W

LiquidAI: LFM2.5-2.6B (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.88/1Mvs$0/1M

Input price

$0.38/1Mvs$0/1M

Context window

1Mvs128k

Gemini 3.7 Flash: 1WLiquidAI: LFM2.5-2.6B (free): 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatLiquidAI: LFM2.5-2.6B (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 3.7 Flash

Larger window (1M).

Screenshots / visionGemini 3.7 Flash

Gemini 3.7 Flash is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	LiquidAI: LFM2.5-2.6B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 3.7 Flash	Larger window (1M).
Screenshots / vision	Gemini 3.7 Flash	Gemini 3.7 Flash is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

LiquidAI: LFM2.5-2.6B (free) output tokens are $0/1M versus $1.88/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 3.7 Flash or LiquidAI: LFM2.5-2.6B (free)?

We do not have TTFT for both models.

Which has the larger context window?

Gemini 3.7 Flash accepts 1M tokens versus 128k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 3.7 Flash and LiquidAI: LFM2.5-2.6B (free) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

LiquidAI: LFM2.5-2.6B (free)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini Flash vs Pro: when Flash is the whole product

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Gemini 3.7 Flash (Aug 13): $0.75/$3.75 intro through Dec 31 2026

Gemini 3.6 Pro: Google’s current Pro-class long-context row

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Gemini 3.7 Flash

LiquidAI: LFM2.5-2.6B (free)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

LiquidAI: LFM2.5-2.6B (free)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini Flash vs Pro: when Flash is the whole product

Gemini 3.6 Flash (Jul 21) now shares the 3.7 intro rate

Gemini 3.7 Flash (Aug 13): $0.75/$3.75 intro through Dec 31 2026

Gemini 3.6 Pro: Google’s current Pro-class long-context row

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Gemini 3.7 Flash

LiquidAI: LFM2.5-2.6B (free)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons