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

MoonshotAI: Kimi K2.5 vs Qwen: Qwen3.6 Flash benchmark

Name: MoonshotAI: Kimi K2.5 vs Qwen: Qwen3.6 Flash AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MoonshotAI: Kimi K2.5 (Moonshot) and Qwen: Qwen3.6 Flash (Alibaba) using the latest snapshots we have as of Aug 17, 2026. Qwen: Qwen3.6 Flash wins on output price at $1.13/1M. Qwen: Qwen3.6 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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Moonshot

MoonshotAI: Kimi K2.5

Auto-discovered from OpenRouter (moonshotai/kimi-k2.5). Preview until a second source matches.

K2.5 MaxElo 1,515$2.8499999999999996/1M out

Alibaba

Qwen: Qwen3.6 Flash

Auto-discovered from OpenRouter (qwen/qwen3.6-flash). Preview until a second source matches.

$1.125/1M out

Model Lineage & Multi-Tier Derivatives🇨🇳 CN Frontier

Kimi Series Family (4 models)

Compare vs Base (Kimi K3)

Kimi K3

Moonshot

Flagship Base

CoT Scaler

Elo

1528

Speed

68 tok/s

Price

$15.00 / 1M

View model →vs this

MoonshotAI: Kimi K2.5

Moonshot

K2.5 Max

CoT Scaler

Elo

1515

Speed

72 tok/s

Price

$2.85 / 1M

-13 Elo-81% cost1.1x speed

Viewing now

MoonshotAI: Kimi K2 0711

Moonshot

K2 Base

Elo

1465

Speed

85 tok/s

Price

$2.30 / 1M

-63 Elo-85% cost1.3x speed

View model →vs this

Kimi Chat 1.5

Moonshot

2M Context

Elo

1420

Speed

95 tok/s

Price

$0.80 / 1M

-108 Elo-95% cost1.4x speed

View model →vs this

MoonshotAI: Kimi K2.5 Inference Compute Profile

Inference-Time Compute & Reasoning EffortDynamic CoT

MoonshotAI: Kimi K2.5 Reasoning Scaler & Token Billing Simulator

Param: thinking_mode

Reasoning models scale test-time compute by generating hidden chain-of-thought (CoT) tokens. These tokens are billed at standard output rates and directly expand latency (TTFT) in exchange for higher GPQA Diamond and SWE-bench Verified problem resolve rates.

Estimated TTFT

270 ms

1.0x (Standard eval)

CoT Thinking Tokens

~2,500

Billed as output tokens

Est. Cost / 1k Calls

$8.27

7.3x base invoice

STEM / SWE Boost

+5.5%

GPQA & SWE-bench scaling

Medium (Deep Reasoning) Operational Profile

Kimi Swarm reasoning trace for long-context planning.

Direct Provider APIMoonshot

"thinking_mode": "medium"

OpenRouter Unified APIUnified Gateway

"reasoning": {
  "effort": "medium",
  "max_tokens": 2500
}

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

Model A

Model B

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.

MoonshotAI: Kimi K2.5 (7)vsQwen: Qwen3.6 Flash (3)

MoonshotAI: Kimi K2.5: 7W (70%)Overall: MoonshotAI: Kimi K2.5Qwen: Qwen3.6 Flash: 3W (30%)

← MoonshotAI: Kimi K2.5Qwen: Qwen3.6 Flash →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs—

Coding Elo

1,520vs—

SWE-bench

71.3%vs—

LiveBench

67.2%vs—

GPQA Diamond

87.6%vs—

MoonshotAI: Kimi K2.5: 5WQwen: Qwen3.6 Flash: 0W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs—

Time to first token

270 msvs—

MoonshotAI: Kimi K2.5: 2WQwen: Qwen3.6 Flash: 0W

Qwen: Qwen3.6 Flash (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$1.13/1M

Input price

$0.57/1Mvs$0.1875/1M

Context window

262kvs1M

MoonshotAI: Kimi K2.5: 0WQwen: Qwen3.6 Flash: 3W

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 AdvantageMoonshotAI: Kimi K2.5 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

Qwen: Qwen3.6 Flash

$1.72/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,515

EloHigh is better

—

Code Elo

High is better

1,520

Code EloHigh is better

—

LiveBench

High is better

67.2%

LiveBenchHigh is better

—

SWE-bench

High is better

71.3%

SWE-benchHigh is better

—

GPQA

High is better

87.6%

GPQAHigh is better

—

TTFT

Low is better

270 ms

TTFTLow is better

—

Speed

High is better

72 tok/s

SpeedHigh is better

—

In $

Low is better

$0.57 / 1M

In $Low is better

$0.19 / 1M+204%

Out $

Low is better

$2.85 / 1M

Out $Low is better

$1.13 / 1M+153%

Context

High is better

262k

ContextHigh is better

1M+281%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 63% with Qwen: Qwen3.6 Flash

Monthly Volume50M tokens/mo

Quick Presets:

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

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

MoonshotAI: Kimi K2.5$62.70 / mo

In: $19.95Out: $42.75

Qwen: Qwen3.6 Flash$23.44 / mo

In: $6.56Out: $16.88

Estimated Cost Delta

Qwen: Qwen3.6 Flash is estimated to save $39.26/month ($471/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen: Qwen3.6 Flash:Pick Qwen: Qwen3.6 Flash when you are optimizing output cost.
2
Qwen: Qwen3.6 Flash:Pick Qwen: Qwen3.6 Flash for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatQwen: Qwen3.6 Flash

Lower output list price ($1.13/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen: Qwen3.6 Flash

Larger window (1M).

Screenshots / visionMoonshotAI: Kimi K2.5

MoonshotAI: Kimi K2.5 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	Qwen: Qwen3.6 Flash	Lower output list price ($1.13/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen: Qwen3.6 Flash	Larger window (1M).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

Moonshot

MoonshotAI: Kimi K2.5

Elo 1,515

LiveBench67.2%

SWE-bench71.3%

Speed72 tok/s

Output cost$2.85/1M

Alibaba

Qwen: Qwen3.6 Flash

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$1.13/1M

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?: 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, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?: 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?: Qwen: Qwen3.6 Flash output tokens are $1.13/1M versus $2.85/1M. Input prices and retry rates still move the real bill.
Which is faster, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?: We do not have TTFT for both models.
Which has the larger context window?: Qwen: Qwen3.6 Flash accepts 1M tokens versus 262k.
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. MoonshotAI: Kimi K2.5 and Qwen: Qwen3.6 Flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All MoonshotAI: Kimi K2.5 matchups →|All Qwen: Qwen3.6 Flash matchups →

MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)Qwen 3 Max vs MoonshotAI: Kimi K2.5 Qwen QwQ 32B vs MoonshotAI: Kimi K2.5 Qwen 2.5 Plus vs MoonshotAI: Kimi K2.5 Claude Sonnet 4.5 vs MoonshotAI: Kimi K2.5

MoonshotAI: Kimi K2.5 vs Qwen: Qwen3.6 Flash benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MoonshotAI: Kimi K2.5 (7)vsQwen: Qwen3.6 Flash (3)

MoonshotAI: Kimi K2.5: 7W (70%)Overall: MoonshotAI: Kimi K2.5Qwen: Qwen3.6 Flash: 3W (30%)

← MoonshotAI: Kimi K2.5Qwen: Qwen3.6 Flash →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs—

Coding Elo

1,520vs—

SWE-bench

71.3%vs—

LiveBench

67.2%vs—

GPQA Diamond

87.6%vs—

MoonshotAI: Kimi K2.5: 5WQwen: Qwen3.6 Flash: 0W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs—

Time to first token

270 msvs—

MoonshotAI: Kimi K2.5: 2WQwen: Qwen3.6 Flash: 0W

Qwen: Qwen3.6 Flash (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$1.13/1M

Input price

$0.57/1Mvs$0.1875/1M

Context window

262kvs1M

MoonshotAI: Kimi K2.5: 0WQwen: Qwen3.6 Flash: 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatQwen: Qwen3.6 Flash

Lower output list price ($1.13/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen: Qwen3.6 Flash

Larger window (1M).

Screenshots / visionMoonshotAI: Kimi K2.5

MoonshotAI: Kimi K2.5 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	Qwen: Qwen3.6 Flash	Lower output list price ($1.13/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen: Qwen3.6 Flash	Larger window (1M).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?

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, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?

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?

Qwen: Qwen3.6 Flash output tokens are $1.13/1M versus $2.85/1M. Input prices and retry rates still move the real bill.

Which is faster, MoonshotAI: Kimi K2.5 or Qwen: Qwen3.6 Flash?

We do not have TTFT for both models.

Which has the larger context window?

Qwen: Qwen3.6 Flash accepts 1M tokens versus 262k.

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. MoonshotAI: Kimi K2.5 and Qwen: Qwen3.6 Flash Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.