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

Claude Fable 5 vs MoonshotAI: Kimi K2.7 Code (batch) benchmark

Name: Claude Fable 5 vs MoonshotAI: Kimi K2.7 Code (batch) AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Claude Fable 5 (Anthropic) and MoonshotAI: Kimi K2.7 Code (batch) (Moonshot) using the latest snapshots we have as of Aug 17, 2026. MoonshotAI: Kimi K2.7 Code (batch) wins on output price at $2/1M. Claude Fable 5 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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Anthropic

Claude Fable 5

Anthropic top-tier long-horizon model. Official API $10/$50 per 1M tokens (Claude Platform pricing, Aug 2026).

Elo 1,616$50/1M out

Moonshot

MoonshotAI: Kimi K2.7 Code (batch)

Auto-discovered from OpenRouter (moonshotai/kimi-k2.7-code:batch). Preview until a second source matches.

$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.

Claude Fable 5 (8)vsMoonshotAI: Kimi K2.7 Code (batch) (2)

Claude Fable 5: 8W (80%)Overall: Claude Fable 5MoonshotAI: Kimi K2.7 Code (batch): 2W (20%)

← Claude Fable 5MoonshotAI: Kimi K2.7 Code (batch) →

Claude Fable 5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,616vs—

Coding Elo

1,622vs—

SWE-bench

80%vs—

LiveBench

75.2%vs—

GPQA Diamond

87.6%vs—

Claude Fable 5: 5WMoonshotAI: Kimi K2.7 Code (batch): 0W

Claude Fable 5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

58 tok/svs—

Time to first token

340 msvs—

Claude Fable 5: 2WMoonshotAI: Kimi K2.7 Code (batch): 0W

MoonshotAI: Kimi K2.7 Code (batch) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$50/1Mvs$2/1M

Input price

$10/1Mvs$0.48/1M

Context window

1Mvs262k

Claude Fable 5: 1WMoonshotAI: Kimi K2.7 Code (batch): 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 AdvantageClaude Fable 5 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

MoonshotAI: Kimi K2.7 Code (batch)

$48.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,616

EloHigh is better

—

Code Elo

High is better

1,622

Code EloHigh is better

—

LiveBench

High is better

75.2%

LiveBenchHigh is better

—

SWE-bench

High is better

80%

SWE-benchHigh is better

—

GPQA

High is better

87.6%

GPQAHigh is better

—

TTFT

Low is better

340 ms

TTFTLow is better

—

Speed

High is better

58 tok/s

SpeedHigh is better

—

In $

Low is better

$10/1M

In $Low is better

$0.48/1M+2005%

Out $

Low is better

$50/1M

Out $Low is better

$2/1M+2400%

Context

High is better

+281%1M

ContextHigh is better

262k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 96% with MoonshotAI: Kimi K2.7 Code (batch)

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Claude Fable 5$1,100.00 / mo

In: $350.00Out: $750.00

MoonshotAI: Kimi K2.7 Code (batch)$46.63 / mo

In: $16.63Out: $30.00

Estimated Cost Delta

MoonshotAI: Kimi K2.7 Code (batch) is estimated to save $1,053.38/month ($12,641/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
MoonshotAI: Kimi K2.7 Code (batch):Pick MoonshotAI: Kimi K2.7 Code (batch) when you are optimizing output cost.
2
Claude Fable 5:Pick Claude Fable 5 for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2.7 Code (batch)

Lower output list price ($2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude Fable 5

Larger window (1M).

Screenshots / visionClaude Fable 5

Claude Fable 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	MoonshotAI: Kimi K2.7 Code (batch)	Lower output list price ($2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude Fable 5	Larger window (1M).
Screenshots / vision	Claude Fable 5	Claude Fable 5 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJun 15, 2026

Claude Fable 5: the $10/$50 long-horizon Anthropic SKU

Fable 5 is not Sonnet with extra adjectives. It is the expensive long-horizon row. Read SWE-bench and output price together.

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LIVE

Anthropic

Claude Fable 5

Elo 1,616

LiveBench75.2%

SWE-bench80%

Speed58 tok/s

Output cost$50/1M

Moonshot

MoonshotAI: Kimi K2.7 Code (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$2/1M

Frequently Asked Questions

Which is better overall, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?: 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, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?: 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?: MoonshotAI: Kimi K2.7 Code (batch) output tokens are $2/1M versus $50/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?: We do not have TTFT for both models.
Which has the larger context window?: Claude Fable 5 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. Claude Fable 5 and MoonshotAI: Kimi K2.7 Code (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Claude Fable 5 matchups →|All MoonshotAI: Kimi K2.7 Code (batch) matchups →

Claude Opus 5 vs Claude Fable 5 Claude Opus 4.8 vs Claude Fable 5 Claude Opus 4.6 vs Claude Fable 5 Claude Opus 4.5 vs Claude Fable 5 Claude Sonnet 5 vs Claude Fable 5 Kimi K3 vs Claude Fable 5

Claude Fable 5 vs MoonshotAI: Kimi K2.7 Code (batch) benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Claude Fable 5 (8)vsMoonshotAI: Kimi K2.7 Code (batch) (2)

Claude Fable 5: 8W (80%)Overall: Claude Fable 5MoonshotAI: Kimi K2.7 Code (batch): 2W (20%)

← Claude Fable 5MoonshotAI: Kimi K2.7 Code (batch) →

Claude Fable 5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,616vs—

Coding Elo

1,622vs—

SWE-bench

80%vs—

LiveBench

75.2%vs—

GPQA Diamond

87.6%vs—

Claude Fable 5: 5WMoonshotAI: Kimi K2.7 Code (batch): 0W

Claude Fable 5 (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

58 tok/svs—

Time to first token

340 msvs—

Claude Fable 5: 2WMoonshotAI: Kimi K2.7 Code (batch): 0W

MoonshotAI: Kimi K2.7 Code (batch) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$50/1Mvs$2/1M

Input price

$10/1Mvs$0.48/1M

Context window

1Mvs262k

Claude Fable 5: 1WMoonshotAI: Kimi K2.7 Code (batch): 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMoonshotAI: Kimi K2.7 Code (batch)

Lower output list price ($2/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGClaude Fable 5

Larger window (1M).

Screenshots / visionClaude Fable 5

Claude Fable 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	MoonshotAI: Kimi K2.7 Code (batch)	Lower output list price ($2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Claude Fable 5	Larger window (1M).
Screenshots / vision	Claude Fable 5	Claude Fable 5 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?

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, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?

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?

MoonshotAI: Kimi K2.7 Code (batch) output tokens are $2/1M versus $50/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude Fable 5 or MoonshotAI: Kimi K2.7 Code (batch)?

We do not have TTFT for both models.

Which has the larger context window?

Claude Fable 5 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. Claude Fable 5 and MoonshotAI: Kimi K2.7 Code (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

MoonshotAI: Kimi K2.7 Code (batch)

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Claude Fable 5: the $10/$50 long-horizon Anthropic SKU

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Claude Fable 5

MoonshotAI: Kimi K2.7 Code (batch)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

MoonshotAI: Kimi K2.7 Code (batch)

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Claude Fable 5: the $10/$50 long-horizon Anthropic SKU

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Claude Fable 5

MoonshotAI: Kimi K2.7 Code (batch)

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons