Pairwise benchmark snapshot · Aug 16, 2026

MoonshotAI: Kimi K2.5 vs Qwen QwQ 32B benchmark

Name: MoonshotAI: Kimi K2.5 vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MoonshotAI: Kimi K2.5 (Moonshot) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, MoonshotAI: Kimi K2.5 is ahead by 20 points (1,515 vs 1,495; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, MoonshotAI: Kimi K2.5 resolves 71.3% versus 67.5% (seed-bootstrap (Aug 1, 2026)). MoonshotAI: Kimi K2.5 streams faster (72 tok/s) while Qwen QwQ 32B is the cheaper output token ($1.2/1M). MoonshotAI: Kimi K2.5 has the larger context window (262k 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.

Elo 1,515$2.8499999999999996/1M out

Alibaba

Qwen QwQ 32B

Alibaba specialized open reasoning model competing with frontier closed reasoning models.

Elo 1,495$1.2/1M out

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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 (6)vsQwen QwQ 32B (3)

MoonshotAI: Kimi K2.5: 6W (67%)Overall: MoonshotAI: Kimi K2.5Qwen QwQ 32B: 3W (33%)

← MoonshotAI: Kimi K2.51 tiesQwen QwQ 32B →

MoonshotAI: Kimi K2.5 (3/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs1,495

Coding Elo

1,520vs1,520

SWE-bench

71.3%vs67.5%

LiveBench

67.2%vs68%

GPQA Diamond

87.6%vs83.2%

MoonshotAI: Kimi K2.5: 3WQwen QwQ 32B: 1W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs68 tok/s

Time to first token

270 msvs320 ms

MoonshotAI: Kimi K2.5: 2WQwen QwQ 32B: 0W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$1.2/1M

Input price

$0.57/1Mvs$0.3/1M

Context window

262kvs131k

MoonshotAI: Kimi K2.5: 1WQwen QwQ 32B: 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 AdvantageMoonshotAI: Kimi K2.5 5/6

Preference Elo

MoonshotAI: Kimi K2.5

20 pts advantage

Throughput Speed

MoonshotAI: Kimi K2.5

4 tok/s faster

Price Efficiency

Qwen QwQ 32B

$1.65/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+1%1,515

EloHigh is better

1,495

Code Elo

High is better

1,520

Code EloHigh is better

1,520

LiveBench

High is better

67.2%

LiveBenchHigh is better

68%+1%

SWE-bench

High is better

+6%71.3%

SWE-benchHigh is better

67.5%

GPQA

High is better

+5%87.6%

GPQAHigh is better

83.2%

TTFT

Low is better

+19%270 ms

TTFTLow is better

320 ms

Speed

High is better

+6%72 tok/s

SpeedHigh is better

68 tok/s

In $

Low is better

$0.57/1M

In $Low is better

$0.3/1M+90%

Out $

Low is better

$2.85/1M

Out $Low is better

$1.2/1M+137%

Context

High is better

+100%262k

ContextHigh is better

131k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 55% with Qwen QwQ 32B

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 QwQ 32B$28.50 / mo

In: $10.50Out: $18.00

Estimated Cost Delta

Qwen QwQ 32B is estimated to save $34.20/month ($410/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
MoonshotAI: Kimi K2.5:Pick MoonshotAI: Kimi K2.5 when repo-level coding accuracy is the constraint.
2
Qwen QwQ 32B:Pick Qwen QwQ 32B when you are optimizing output cost.
3
MoonshotAI: Kimi K2.5:Pick MoonshotAI: Kimi K2.5 when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsMoonshotAI: Kimi K2.5

Higher SWE-bench (71.3%).

High-volume chatQwen QwQ 32B

Lower output list price ($1.2/1M).

Voice / low-latency UIMoonshotAI: Kimi K2.5

Lower TTFT (270 ms).

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

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	MoonshotAI: Kimi K2.5	Higher SWE-bench (71.3%).
High-volume chat	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	MoonshotAI: Kimi K2.5	Lower TTFT (270 ms).
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

Moonshot

MoonshotAI: Kimi K2.5

Elo 1,515

LiveBench67.2%

SWE-bench71.3%

Speed72 tok/s

Output cost$2.85/1M

Alibaba

Qwen QwQ 32B

Elo 1,495

LiveBench68%

SWE-bench67.5%

Speed68 tok/s

Output cost$1.2/1M

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or Qwen QwQ 32B?: MoonshotAI: Kimi K2.5 has the higher preference Elo in our latest snapshot (1,515). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, MoonshotAI: Kimi K2.5 or Qwen QwQ 32B?: MoonshotAI: Kimi K2.5 leads SWE-bench at 71.3% vs 67.5%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Qwen QwQ 32B output tokens are $1.2/1M versus $2.85/1M. Input prices and retry rates still move the real bill.
Which is faster, MoonshotAI: Kimi K2.5 or Qwen QwQ 32B?: MoonshotAI: Kimi K2.5 has the lower time-to-first-token (270 ms vs 320 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: MoonshotAI: Kimi K2.5 accepts 262k tokens versus 131k.
Can I self-host either model?: Qwen QwQ 32B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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 QwQ 32B 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 QwQ 32B matchups →

MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen QwQ 32B vs Qwen 3 Max (next qwen)Qwen 3 Max vs MoonshotAI: Kimi K2.5 MoonshotAI: Kimi K2 0711 vs Qwen QwQ 32B

MoonshotAI: Kimi K2.5 vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MoonshotAI: Kimi K2.5 (6)vsQwen QwQ 32B (3)

MoonshotAI: Kimi K2.5: 6W (67%)Overall: MoonshotAI: Kimi K2.5Qwen QwQ 32B: 3W (33%)

← MoonshotAI: Kimi K2.51 tiesQwen QwQ 32B →

MoonshotAI: Kimi K2.5 (3/5)

Intelligence & Reasoning

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

Preference Elo

1,515vs1,495

Coding Elo

1,520vs1,520

SWE-bench

71.3%vs67.5%

LiveBench

67.2%vs68%

GPQA Diamond

87.6%vs83.2%

MoonshotAI: Kimi K2.5: 3WQwen QwQ 32B: 1W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

72 tok/svs68 tok/s

Time to first token

270 msvs320 ms

MoonshotAI: Kimi K2.5: 2WQwen QwQ 32B: 0W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.85/1Mvs$1.2/1M

Input price

$0.57/1Mvs$0.3/1M

Context window

262kvs131k

MoonshotAI: Kimi K2.5: 1WQwen QwQ 32B: 2W

Recommended Workload Routing

Repo / coding agentsMoonshotAI: Kimi K2.5

Higher SWE-bench (71.3%).

High-volume chatQwen QwQ 32B

Lower output list price ($1.2/1M).

Voice / low-latency UIMoonshotAI: Kimi K2.5

Lower TTFT (270 ms).

Long-document RAGMoonshotAI: Kimi K2.5

Larger window (262k).

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	MoonshotAI: Kimi K2.5	Higher SWE-bench (71.3%).
High-volume chat	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	MoonshotAI: Kimi K2.5	Lower TTFT (270 ms).
Long-document RAG	MoonshotAI: Kimi K2.5	Larger window (262k).
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 QwQ 32B?

MoonshotAI: Kimi K2.5 has the higher preference Elo in our latest snapshot (1,515). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, MoonshotAI: Kimi K2.5 or Qwen QwQ 32B?

MoonshotAI: Kimi K2.5 leads SWE-bench at 71.3% vs 67.5%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Qwen QwQ 32B output tokens are $1.2/1M versus $2.85/1M. Input prices and retry rates still move the real bill.

Which is faster, MoonshotAI: Kimi K2.5 or Qwen QwQ 32B?

MoonshotAI: Kimi K2.5 has the lower time-to-first-token (270 ms vs 320 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

MoonshotAI: Kimi K2.5 accepts 262k tokens versus 131k.

Can I self-host either model?

Qwen QwQ 32B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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 QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.