Pairwise benchmark snapshot · Aug 1, 2026

Gemini 2.0 Flash Thinking vs Kimi Chat 1.5 benchmark

Name: Gemini 2.0 Flash Thinking vs Kimi Chat 1.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 2.0 Flash Thinking (Google) and Kimi Chat 1.5 (Moonshot) using the latest snapshots we have as of Aug 1, 2026. On preference Elo, Gemini 2.0 Flash Thinking is ahead by 70 points (1,490 vs 1,420; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Gemini 2.0 Flash Thinking resolves 66.8% versus 51% (seed-bootstrap (Aug 1, 2026)). Gemini 2.0 Flash Thinking streams faster (115 tok/s) while Gemini 2.0 Flash Thinking is the cheaper output token ($0.4/1M). Kimi Chat 1.5 has the larger context window (2M 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

Moonshot

Kimi Chat 1.5

Moonshot ultra-long context model supporting up to 2 million tokens per request.

Elo 1,420$0.8/1M out

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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 (8)vsKimi Chat 1.5 (2)

Gemini 2.0 Flash Thinking: 8W (80%)Overall: Gemini 2.0 Flash ThinkingKimi Chat 1.5: 2W (20%)

← Gemini 2.0 Flash ThinkingKimi Chat 1.5 →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,420

Coding Elo

1,515vs1,390

SWE-bench

66.8%vs51%

LiveBench

67%vs58%

GPQA Diamond

81%vs71.5%

Gemini 2.0 Flash Thinking: 5WKimi Chat 1.5: 0W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs95 tok/s

Time to first token

220 msvs210 ms

Gemini 2.0 Flash Thinking: 1WKimi Chat 1.5: 1W

Gemini 2.0 Flash Thinking (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$0.8/1M

Input price

$0.1/1Mvs$0.2/1M

Context window

1Mvs2M

Gemini 2.0 Flash Thinking: 2WKimi Chat 1.5: 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 5/6

Preference Elo

Gemini 2.0 Flash Thinking

70 pts advantage

Throughput Speed

Gemini 2.0 Flash Thinking

20 tok/s faster

Price Efficiency

Gemini 2.0 Flash Thinking

$0.40/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+5%1,490

EloHigh is better

1,420

Code Elo

High is better

+9%1,515

Code EloHigh is better

1,390

LiveBench

High is better

+16%67%

LiveBenchHigh is better

58%

SWE-bench

High is better

+31%66.8%

SWE-benchHigh is better

51%

GPQA

High is better

+13%81%

GPQAHigh is better

71.5%

TTFT

Low is better

220 ms

TTFTLow is better

210 ms+5%

Speed

High is better

+21%115 tok/s

SpeedHigh is better

95 tok/s

In $

Low is better

+100%$0.1/1M

In $Low is better

$0.2/1M

Out $

Low is better

+100%$0.4/1M

Out $Low is better

$0.8/1M

Context

High is better

ContextHigh is better

2M+91%

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 50% with Gemini 2.0 Flash Thinking

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

Kimi Chat 1.5$19.00 / mo

In: $7.00Out: $12.00

Estimated Cost Delta

Gemini 2.0 Flash Thinking is estimated to save $9.50/month ($114/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
Kimi Chat 1.5:Pick Kimi Chat 1.5 when time-to-first-token matters more than peak Elo.
3
Kimi Chat 1.5:Pick Kimi Chat 1.5 for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIKimi Chat 1.5

Lower TTFT (210 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

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	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Kimi Chat 1.5	Lower TTFT (210 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
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

Moonshot

Kimi Chat 1.5

Elo 1,420

LiveBench58%

SWE-bench51%

Speed95 tok/s

Output cost$0.8/1M

Frequently Asked Questions

Which is better overall, Gemini 2.0 Flash Thinking or Kimi Chat 1.5?: 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 Kimi Chat 1.5?: Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 51%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $0.8/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 2.0 Flash Thinking or Kimi Chat 1.5?: Kimi Chat 1.5 has the lower time-to-first-token (210 ms vs 220 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Kimi Chat 1.5 accepts 2M tokens versus 1M.
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 Kimi Chat 1.5 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 Kimi Chat 1.5 matchups →

Gemini 2.0 Flash Thinking vs Gemini 2.5 Flash (next gemini-flash)Kimi Chat 1.5 vs MoonshotAI: Kimi K2 0711 (next kimi)Gemini 3 Flash vs Gemini 2.0 Flash Thinking Gemini 3.6 Flash vs Gemini 2.0 Flash Thinking Kimi K3 vs Gemini 2.0 Flash Thinking Gemini 3.7 Flash vs Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking vs Kimi Chat 1.5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.0 Flash Thinking (8)vsKimi Chat 1.5 (2)

Gemini 2.0 Flash Thinking: 8W (80%)Overall: Gemini 2.0 Flash ThinkingKimi Chat 1.5: 2W (20%)

← Gemini 2.0 Flash ThinkingKimi Chat 1.5 →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,420

Coding Elo

1,515vs1,390

SWE-bench

66.8%vs51%

LiveBench

67%vs58%

GPQA Diamond

81%vs71.5%

Gemini 2.0 Flash Thinking: 5WKimi Chat 1.5: 0W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs95 tok/s

Time to first token

220 msvs210 ms

Gemini 2.0 Flash Thinking: 1WKimi Chat 1.5: 1W

Gemini 2.0 Flash Thinking (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$0.8/1M

Input price

$0.1/1Mvs$0.2/1M

Context window

1Mvs2M

Gemini 2.0 Flash Thinking: 2WKimi Chat 1.5: 1W

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIKimi Chat 1.5

Lower TTFT (210 ms).

Long-document RAGKimi Chat 1.5

Larger window (2M).

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	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Kimi Chat 1.5	Lower TTFT (210 ms).
Long-document RAG	Kimi Chat 1.5	Larger window (2M).
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 Kimi Chat 1.5?

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 Kimi Chat 1.5?

Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 51%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $0.8/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 2.0 Flash Thinking or Kimi Chat 1.5?

Kimi Chat 1.5 has the lower time-to-first-token (210 ms vs 220 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Kimi Chat 1.5 accepts 2M tokens versus 1M.

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 Kimi Chat 1.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.