Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

Thinking Machines: Inkling (batch) vs MoonshotAI: Kimi K2.5 benchmark

Name: Thinking Machines: Inkling (batch) vs MoonshotAI: Kimi K2.5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Thinking Machines: Inkling (batch) (thinkingmachines) and MoonshotAI: Kimi K2.5 (Moonshot) using the latest snapshots we have as of Aug 16, 2026. Thinking Machines: Inkling (batch) wins on output price at $2.03/1M. Thinking Machines: Inkling (batch) has the larger context window (524k 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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thinkingmachines

Thinking Machines: Inkling (batch)

Auto-discovered from OpenRouter (thinkingmachines/inkling:batch). Preview until a second source matches.

$2.025/1M out

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

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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.

Thinking Machines: Inkling (batch) (3)vsMoonshotAI: Kimi K2.5 (7)

Thinking Machines: Inkling (batch): 3W (30%)Overall: MoonshotAI: Kimi K2.5MoonshotAI: Kimi K2.5: 7W (70%)

← Thinking Machines: Inkling (batch)MoonshotAI: Kimi K2.5 →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,515

Coding Elo

—vs1,520

SWE-bench

—vs71.3%

LiveBench

—vs67.2%

GPQA Diamond

—vs87.6%

Thinking Machines: Inkling (batch): 0WMoonshotAI: Kimi K2.5: 5W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs72 tok/s

Time to first token

—vs270 ms

Thinking Machines: Inkling (batch): 0WMoonshotAI: Kimi K2.5: 2W

Thinking Machines: Inkling (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.03/1Mvs$2.85/1M

Input price

$0.5/1Mvs$0.57/1M

Context window

524kvs262k

Thinking Machines: Inkling (batch): 3WMoonshotAI: Kimi K2.5: 0W

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

Price Efficiency

Thinking Machines: Inkling (batch)

$0.82/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,515

Code Elo

High is better

—

Code EloHigh is better

1,520

LiveBench

High is better

—

LiveBenchHigh is better

67.2%

SWE-bench

High is better

—

SWE-benchHigh is better

71.3%

GPQA

High is better

—

GPQAHigh is better

87.6%

TTFT

Low is better

—

TTFTLow is better

270 ms

Speed

High is better

—

SpeedHigh is better

72 tok/s

In $

Low is better

+14%$0.5/1M

In $Low is better

$0.57/1M

Out $

Low is better

+41%$2.03/1M

Out $Low is better

$2.85/1M

Context

High is better

+100%524k

ContextHigh is better

262k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 24% with Thinking Machines: Inkling (batch)

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Thinking Machines: Inkling (batch)$47.88 / mo

In: $17.50Out: $30.38

MoonshotAI: Kimi K2.5$62.70 / mo

In: $19.95Out: $42.75

Estimated Cost Delta

Thinking Machines: Inkling (batch) is estimated to save $14.82/month ($178/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Thinking Machines: Inkling (batch):Pick Thinking Machines: Inkling (batch) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatThinking Machines: Inkling (batch)

Lower output list price ($2.03/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGThinking Machines: Inkling (batch)

Larger window (524k).

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	Thinking Machines: Inkling (batch)	Lower output list price ($2.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Thinking Machines: Inkling (batch)	Larger window (524k).
Screenshots / vision	MoonshotAI: Kimi K2.5	MoonshotAI: Kimi K2.5 is the side marked multimodal in the catalog.

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LIVE

thinkingmachines

Thinking Machines: Inkling (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$2.03/1M

Moonshot

MoonshotAI: Kimi K2.5

Elo 1,515

LiveBench67.2%

SWE-bench71.3%

Speed72 tok/s

Output cost$2.85/1M

Frequently Asked Questions

Which is better overall, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?: 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, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?: 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?: Thinking Machines: Inkling (batch) output tokens are $2.03/1M versus $2.85/1M. Input prices and retry rates still move the real bill.
Which is faster, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?: We do not have TTFT for both models.
Which has the larger context window?: Thinking Machines: Inkling (batch) accepts 524k 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. Thinking Machines: Inkling (batch) and MoonshotAI: Kimi K2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Thinking Machines: Inkling (batch) matchups →|All MoonshotAI: Kimi K2.5 matchups →

MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)Kimi Chat 1.5 vs MoonshotAI: Kimi K2.5 Claude Opus 4.5 vs MoonshotAI: Kimi K2.5 Claude Opus 4.6 vs MoonshotAI: Kimi K2.5 Claude Sonnet 4.5 vs MoonshotAI: Kimi K2.5

Thinking Machines: Inkling (batch) vs MoonshotAI: Kimi K2.5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Thinking Machines: Inkling (batch) (3)vsMoonshotAI: Kimi K2.5 (7)

Thinking Machines: Inkling (batch): 3W (30%)Overall: MoonshotAI: Kimi K2.5MoonshotAI: Kimi K2.5: 7W (70%)

← Thinking Machines: Inkling (batch)MoonshotAI: Kimi K2.5 →

MoonshotAI: Kimi K2.5 (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,515

Coding Elo

—vs1,520

SWE-bench

—vs71.3%

LiveBench

—vs67.2%

GPQA Diamond

—vs87.6%

Thinking Machines: Inkling (batch): 0WMoonshotAI: Kimi K2.5: 5W

MoonshotAI: Kimi K2.5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs72 tok/s

Time to first token

—vs270 ms

Thinking Machines: Inkling (batch): 0WMoonshotAI: Kimi K2.5: 2W

Thinking Machines: Inkling (batch) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.03/1Mvs$2.85/1M

Input price

$0.5/1Mvs$0.57/1M

Context window

524kvs262k

Thinking Machines: Inkling (batch): 3WMoonshotAI: Kimi K2.5: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatThinking Machines: Inkling (batch)

Lower output list price ($2.03/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGThinking Machines: Inkling (batch)

Larger window (524k).

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	Thinking Machines: Inkling (batch)	Lower output list price ($2.03/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Thinking Machines: Inkling (batch)	Larger window (524k).
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, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?

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, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?

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?

Thinking Machines: Inkling (batch) output tokens are $2.03/1M versus $2.85/1M. Input prices and retry rates still move the real bill.

Which is faster, Thinking Machines: Inkling (batch) or MoonshotAI: Kimi K2.5?

We do not have TTFT for both models.

Which has the larger context window?

Thinking Machines: Inkling (batch) accepts 524k 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. Thinking Machines: Inkling (batch) and MoonshotAI: Kimi K2.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.