Pairwise benchmark snapshot · Aug 1, 2026

Gemini 2.0 Flash Thinking vs Yi-Lightning benchmark

Name: Gemini 2.0 Flash Thinking vs Yi-Lightning AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 2.0 Flash Thinking (Google) and Yi-Lightning (01.AI) using the latest snapshots we have as of Aug 1, 2026. On preference Elo, Gemini 2.0 Flash Thinking is ahead by 15 points (1,490 vs 1,475; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Gemini 2.0 Flash Thinking resolves 66.8% versus 63.4% (seed-bootstrap (Aug 1, 2026)). Yi-Lightning streams faster (130 tok/s) while Yi-Lightning is the cheaper output token ($0.14/1M). Gemini 2.0 Flash Thinking 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 2.0 Flash Thinking

Google experimental reasoning model that visualizes thoughts in real-time.

Elo 1,490$0.4/1M out

01.AI

Yi-Lightning

01.AI ultra-fast reasoning model delivering top LiveBench efficiency.

Elo 1,475$0.14/1M out

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Model A

Model B

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.0 Flash Thinking (7)vsYi-Lightning (3)

Gemini 2.0 Flash Thinking: 7W (70%)Overall: Gemini 2.0 Flash ThinkingYi-Lightning: 3W (30%)

← Gemini 2.0 Flash ThinkingYi-Lightning →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,475

Coding Elo

1,515vs1,480

SWE-bench

66.8%vs63.4%

LiveBench

67%vs65%

GPQA Diamond

81%vs78%

Gemini 2.0 Flash Thinking: 5WYi-Lightning: 0W

Yi-Lightning (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs130 tok/s

Time to first token

220 msvs150 ms

Gemini 2.0 Flash Thinking: 0WYi-Lightning: 2W

Gemini 2.0 Flash Thinking (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$0.14/1M

Input price

$0.1/1Mvs$0.14/1M

Context window

1Mvs16k

Gemini 2.0 Flash Thinking: 2WYi-Lightning: 1W

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 2.0 Flash Thinking 4/6

Preference Elo

Gemini 2.0 Flash Thinking

15 pts advantage

Throughput Speed

Yi-Lightning

15 tok/s faster

Price Efficiency

Yi-Lightning

$0.26/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+1%1,490

EloHigh is better

1,475

Code Elo

High is better

+2%1,515

Code EloHigh is better

1,480

LiveBench

High is better

+3%67%

LiveBenchHigh is better

65%

SWE-bench

High is better

+5%66.8%

SWE-benchHigh is better

63.4%

GPQA

High is better

+4%81%

GPQAHigh is better

78%

TTFT

Low is better

220 ms

TTFTLow is better

150 ms+47%

Speed

High is better

115 tok/s

SpeedHigh is better

130 tok/s+13%

In $

Low is better

+40%$0.1/1M

In $Low is better

$0.14/1M

Out $

Low is better

$0.4/1M

Out $Low is better

$0.14/1M+186%

Context

High is better

+6300%1M

ContextHigh is better

16k

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 26% with Yi-Lightning

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Gemini 2.0 Flash Thinking$9.50 / mo

In: $3.50Out: $6.00

Yi-Lightning$7.00 / mo

In: $4.90Out: $2.10

Estimated Cost Delta

Yi-Lightning is estimated to save $2.50/month ($30/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking when repo-level coding accuracy is the constraint.
2
Yi-Lightning:Pick Yi-Lightning when you are optimizing output cost.
3
Yi-Lightning:Pick Yi-Lightning when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatYi-Lightning

Lower output list price ($0.14/1M).

Voice / low-latency UIYi-Lightning

Lower TTFT (150 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Yi-Lightning	Lower output list price ($0.14/1M).
Voice / low-latency UI	Yi-Lightning	Lower TTFT (150 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

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LIVE

Google

Gemini 2.0 Flash Thinking

Elo 1,490

LiveBench67%

SWE-bench66.8%

Speed115 tok/s

Output cost$0.4/1M

01.AI

Yi-Lightning

Elo 1,475

LiveBench65%

SWE-bench63.4%

Speed130 tok/s

Output cost$0.14/1M

Frequently Asked Questions

Which is better overall, Gemini 2.0 Flash Thinking or Yi-Lightning?: Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 2.0 Flash Thinking or Yi-Lightning?: Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 63.4%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Yi-Lightning output tokens are $0.14/1M versus $0.4/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 2.0 Flash Thinking or Yi-Lightning?: Yi-Lightning has the lower time-to-first-token (150 ms vs 220 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 2.0 Flash Thinking accepts 1M tokens versus 16k.
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 2.0 Flash Thinking and Yi-Lightning Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 2.0 Flash Thinking matchups →|All Yi-Lightning matchups →

Gemini 2.0 Flash Thinking vs Gemini 2.5 Flash (next gemini-flash)Yi-Lightning vs Yi-Large (previous other)Yi-Lightning vs Ernie 4.5 Turbo (next other)Gemini 3 Flash vs Gemini 2.0 Flash Thinking Gemini 3.6 Flash vs Gemini 2.0 Flash Thinking Gemini 3.7 Flash vs Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking vs Yi-Lightning benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.0 Flash Thinking (7)vsYi-Lightning (3)

Gemini 2.0 Flash Thinking: 7W (70%)Overall: Gemini 2.0 Flash ThinkingYi-Lightning: 3W (30%)

← Gemini 2.0 Flash ThinkingYi-Lightning →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,475

Coding Elo

1,515vs1,480

SWE-bench

66.8%vs63.4%

LiveBench

67%vs65%

GPQA Diamond

81%vs78%

Gemini 2.0 Flash Thinking: 5WYi-Lightning: 0W

Yi-Lightning (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs130 tok/s

Time to first token

220 msvs150 ms

Gemini 2.0 Flash Thinking: 0WYi-Lightning: 2W

Gemini 2.0 Flash Thinking (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$0.14/1M

Input price

$0.1/1Mvs$0.14/1M

Context window

1Mvs16k

Gemini 2.0 Flash Thinking: 2WYi-Lightning: 1W

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatYi-Lightning

Lower output list price ($0.14/1M).

Voice / low-latency UIYi-Lightning

Lower TTFT (150 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Yi-Lightning	Lower output list price ($0.14/1M).
Voice / low-latency UI	Yi-Lightning	Lower TTFT (150 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Gemini 2.0 Flash Thinking or Yi-Lightning?

Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Gemini 2.0 Flash Thinking or Yi-Lightning?

Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 63.4%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Yi-Lightning output tokens are $0.14/1M versus $0.4/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 2.0 Flash Thinking or Yi-Lightning?

Yi-Lightning has the lower time-to-first-token (150 ms vs 220 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 2.0 Flash Thinking accepts 1M tokens versus 16k.

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 2.0 Flash Thinking and Yi-Lightning Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.