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

MoonshotAI: Kimi K2.5 vs Luma UNI 1 Max benchmark

Name: MoonshotAI: Kimi K2.5 vs Luma UNI 1 Max AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares MoonshotAI: Kimi K2.5 (Moonshot) and Luma UNI 1 Max (Luma Labs) using the latest snapshots we have as of Aug 17, 2026. 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 MaxImg Elo 1,515

Luma Labs

Luma UNI 1 Max

Luma Labs universal 3D-aware image synthesis engine with spatial geometry consistency.

Img Elo 1,226$100/1k imgs

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 (0)vsLuma UNI 1 Max (5)

MoonshotAI: Kimi K2.5: 0W (0%)Overall: Luma UNI 1 MaxLuma UNI 1 Max: 5W (100%)

← MoonshotAI: Kimi K2.5Luma UNI 1 Max →

Luma UNI 1 Max (3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Image Elo

—vs1,226

Prompt adherence

—vs90.2%

Text rendering

—vs90%

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 3W

Luma UNI 1 Max (1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Generation time

—vs4.4s

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 1W

Luma UNI 1 Max (1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Price per 1k images

—vs$100/1k

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 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 AdvantageLuma UNI 1 Max 5/6

Image Preference Elo

No shared data

Generation Latency

No shared data

Image Price Efficiency

No shared data

Full Benchmark Score Matrix

—

Img Elo

High is better

—

Img EloHigh is better

1,226

Gen Time

Low is better

—

Gen TimeLow is better

4.4s

Img $

Low is better

—

Img $Low is better

$100/1k

Prompt %

High is better

—

Prompt %High is better

90.2%

Text %

High is better

—

Text %High is better

90%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 100% with MoonshotAI: Kimi K2.5

Monthly Image Production Volume25k images / month (25000 imgs)

Quick Presets:

MoonshotAI: Kimi K2.5$0.00 / mo

Rate: $0/1k

Luma UNI 1 Max$2,500.00 / mo

Rate: $100/1k

Estimated Cost Delta

MoonshotAI: Kimi K2.5 is estimated to save $2,500.00/month ($30,000/year).

Based on 25k images generated

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visioninsufficient data

Both accept images. Defaulting to the higher-Elo side (undefined).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	insufficient data	Both accept images. Defaulting to the higher-Elo side (undefined).

Community Sentiment

Cast Your Matchup Vote

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Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

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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

Luma Labs

Luma UNI 1 Max

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost—

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or Luma UNI 1 Max?: 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 Luma UNI 1 Max?: 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?: List prices are missing for at least one model.
Which is faster, MoonshotAI: Kimi K2.5 or Luma UNI 1 Max?: We do not have TTFT for both models.
Which has the larger context window?: Context window is missing for at least one model.
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 Luma UNI 1 Max 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 Luma UNI 1 Max matchups →

MoonshotAI: Kimi K2.5 vs MoonshotAI: Kimi K2 0711 (previous kimi)MoonshotAI: Kimi K2.5 vs Kimi K3 (next kimi)Luma UNI 1 Max vs HiDream-O1-Image-1.5 (next other)Qwen 3 Max vs MoonshotAI: Kimi K2.5 Claude Sonnet 4.5 vs MoonshotAI: Kimi K2.5 Gemini 3.6 Flash vs MoonshotAI: Kimi K2.5

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

MoonshotAI: Kimi K2.5 (0)vsLuma UNI 1 Max (5)

MoonshotAI: Kimi K2.5: 0W (0%)Overall: Luma UNI 1 MaxLuma UNI 1 Max: 5W (100%)

← MoonshotAI: Kimi K2.5Luma UNI 1 Max →

Luma UNI 1 Max (3/3)

Visual Quality & Adherence

Arena Preference Elo, prompt fidelity & typography score

Image Elo

—vs1,226

Prompt adherence

—vs90.2%

Text rendering

—vs90%

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 3W

Luma UNI 1 Max (1/1)

Generation Latency

Time to render full-resolution image snapshot (seconds)

Generation time

—vs4.4s

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 1W

Luma UNI 1 Max (1/1)

Cost Efficiency

API inference cost per 1,000 generated images

Price per 1k images

—vs$100/1k

MoonshotAI: Kimi K2.5: 0WLuma UNI 1 Max: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatinsufficient data

Need list prices.

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGinsufficient data

Need context sizes.

Screenshots / visioninsufficient data

Both accept images. Defaulting to the higher-Elo side (undefined).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	insufficient data	Need list prices.
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	insufficient data	Need context sizes.
Screenshots / vision	insufficient data	Both accept images. Defaulting to the higher-Elo side (undefined).

Frequently Asked Questions

Which is better overall, MoonshotAI: Kimi K2.5 or Luma UNI 1 Max?

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 Luma UNI 1 Max?

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?

List prices are missing for at least one model.

Which is faster, MoonshotAI: Kimi K2.5 or Luma UNI 1 Max?

We do not have TTFT for both models.

Which has the larger context window?

Context window is missing for at least one model.

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 Luma UNI 1 Max Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.