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Kimi K2 Thinking vs Muse Spark 1.3 Contributor

Kimi K2 Thinking

Moonshot AI

40#359
vs
Signal-by-Signal Comparison
SignalKimi K2 ThinkingDeltaMuse Spark 1.3 Contributor
Capabilities
67
-33
100
Pricing
98
-2
100
Context window size
86
-9
96
Recency
75
-25
100
Output Capacity
80
-16
96
Overall Result
0 wins
of 5
5 wins
Muse Spark 1.3 Contributor wins 5 of 5 signals

Score History

Score History (32 data points)
Kimi K2 ThinkingMuse Spark 1.3 Contributor
Kimi K2 Thinking

40

current score

Leader

Tied

right now

Muse Spark 1.3 Contributor

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Kimi K2 Thinking

Moonshot AI

Per request$0.001850
Daily$6.17
Monthly$185.00
Annual$2220.00

Muse Spark 1.3 Contributor

meta

Best Value
Per request$0.000200
Daily$0.67
Monthly$20.00
Annual$240.00

Muse Spark 1.3 Contributor saves you $165.00/month

That's $1980.00/year compared to Kimi K2 Thinking at your current usage level of 100K calls/month.

89% cheaper
Choose Muse Spark 1.3 Contributor for cost optimization

Kimi K2 Thinking pricing:
Input:$0.60/M tokens
Output:$2.50/M tokens
Muse Spark 1.3 Contributor pricing:
Input:$0.10/M tokens
Output:$0.20/M tokens
Tie
Kimi K2 Thinking

Moonshot AI

40

Composite Score

Tie
Muse Spark 1.3 Contributor

meta

40

Composite Score

Signal-by-Signal Comparison
MetricKimi K2 ThinkingMuse Spark 1.3 ContributorWinner
Overall Score
40
40
--
Rank#359#263
Muse Spark 1.3 Contributor
Quality Rank#359#263
Muse Spark 1.3 Contributor
Adoption Rank#359#263
Muse Spark 1.3 Contributor
Parameters------
Context Window262K1049K
Muse Spark 1.3 Contributor
Pricing$0.60/$2.50/M$0.10/$0.20/M--
Signal Scores
Capabilities
67
100
Muse Spark 1.3 Contributor
Pricing
98
100
Muse Spark 1.3 Contributor
Context window size
86
96
Muse Spark 1.3 Contributor
Recency
75
100
Muse Spark 1.3 Contributor
Output Capacity
80
96
Muse Spark 1.3 Contributor
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Kimi K2 ThinkingEntry Level

Scores 40/100 (rank #359), placing it in the top -23% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Muse Spark 1.3 ContributorEntry Level

Scores 40/100 (rank #263), placing it in the top 10% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Kimi K2 Thinking when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose Muse Spark 1.3 Contributor when you need:

  • High-volume production workloads where API costs must be minimized
  • Processing long documents or large codebases (1049K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Kimi K2 Thinking
Input cost$0.60/M tokens
Output cost$2.50/M tokens
Cost per quality point$0.077
Est. monthly (1M tokens/day)$46.50
Muse Spark 1.3 ContributorBest Value
Input cost$0.10/M tokens
Output cost$0.20/M tokens
Cost per quality point$0.007
Est. monthly (1M tokens/day)$4.50

Muse Spark 1.3 Contributor offers 90% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with Muse Spark 1.3 Contributor vs $46.50/month with Kimi K2 Thinking - a $42.00 monthly difference.

Latency & Speed
Kimi K2 ThinkingFaster
Speed score0/100
Muse Spark 1.3 Contributor
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Kimi K2 Thinking

Customer support chatbot

Suitable for user-facing chat with competitive response times. Muse Spark 1.3 Contributor also offers lower per-token costs for high-volume support

Kimi K2 Thinking

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

Muse Spark 1.3 Contributor

Batch data extraction

Lower output pricing ($0.20/M) reduces costs when processing thousands of records daily

Muse Spark 1.3 Contributor

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

Kimi K2 Thinking

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Muse Spark 1.3 Contributor
Which Should You Choose?
Our recommendation:
Kimi K2 Thinking

Kimi K2 Thinking and Muse Spark 1.3 Contributor are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

Kimi K2 Thinking
Recommended

by Moonshot AI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by meta

  • Choose for Cost - 90% lower pricing; better value at scale
Capability Comparison
CapabilityKimi K2 ThinkingMuse Spark 1.3 Contributor
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Kimi K2 Thinking

Moonshot AI

$4.08
estimated monthly cost

Muse Spark 1.3 Contributor

meta

Best Value
$0.4200
estimated monthly cost

Muse Spark 1.3 Contributor saves you $3.66/month

That's 90% cheaper than Kimi K2 Thinking at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterKimi K2 ThinkingMuse Spark 1.3 Contributor
Context Window262K1.0M
Max Output Tokens98,304943,718
Open SourceYesNo
CreatedNov 6, 2025Sep 2, 2026
Last updated: 1h ago

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Kimi K2 Thinking vs Muse Spark 1.3 Contributor (2026) | LM Market Cap