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Muse Spark 1.2 vs Qwen3 Max Thinking

vs
Qwen3 Max Thinking

Alibaba

68#178
Signal-by-Signal Comparison
SignalMuse Spark 1.2DeltaQwen3 Max Thinking
Capabilities
100
+33
67
Pricing
96
0
96
Context window size
96
+10
86
Recency
100
+8
92
Output Capacity
96
+19
77
Benchmarks
0
-69
69
Overall Result
4 wins
of 6
2 wins
Muse Spark 1.2 wins 4 of 6 signals

Score History

Score History (32 data points)
Muse Spark 1.2Qwen3 Max Thinking
Muse Spark 1.2

80.9

current score

Leader

Muse Spark 1.2

right now

Qwen3 Max Thinking

68.2

current score

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

Muse Spark 1.2

meta

Per request$0.003375
Daily$11.25
Monthly$337.50
Annual$4050.00

Qwen3 Max Thinking

Alibaba

Best Value
Per request$0.002730
Daily$9.10
Monthly$273.00
Annual$3276.00

Qwen3 Max Thinking saves you $64.50/month

That's $774.00/year compared to Muse Spark 1.2 at your current usage level of 100K calls/month.

19% cheaper
Choose Qwen3 Max Thinking for cost optimization

Muse Spark 1.2 pricing:
Input:$1.25/M tokens
Output:$4.25/M tokens
Qwen3 Max Thinking pricing:
Input:$0.78/M tokens
Output:$3.90/M tokens
Winner
Muse Spark 1.2

meta

81

Composite Score

Qwen3 Max Thinking

Alibaba

68

Composite Score

Signal-by-Signal Comparison
MetricMuse Spark 1.2Qwen3 Max ThinkingWinner
Overall Score
81
68
Muse Spark 1.2
Rank#83#178
Muse Spark 1.2
Quality Rank#83#178
Muse Spark 1.2
Adoption Rank#83#178
Muse Spark 1.2
Parameters------
Context Window1049K262K
Muse Spark 1.2
Pricing$1.25/$4.25/M$0.78/$3.90/M--
Signal Scores
Capabilities
100
67
Muse Spark 1.2
Pricing
96
96
Qwen3 Max Thinking
Context window size
96
86
Muse Spark 1.2
Recency
100
92
Muse Spark 1.2
Output Capacity
96
77
Muse Spark 1.2
Benchmarks--
69
Qwen3 Max Thinking
Benchmark Head-to-Head(1 benchmarks)
Muse Spark: 0Qwen3 Max: 0
Muse Spark
Qwen3 Max
Normalized 0-100%
MMLU-Pro
-85.7%
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.

Muse Spark 1.2Strong Performer

Scores 81/100 (rank #83), placing it in the top 72% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3 Max ThinkingCompetitive

Scores 68/100 (rank #178), placing it in the top 39% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

Muse Spark 1.2 has a 13-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.

When to Use Each Model

Choose Muse Spark 1.2 when you need:

  • 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

Choose Qwen3 Max Thinking when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Muse Spark 1.2Best Value
Input cost$1.25/M tokens
Output cost$4.25/M tokens
Cost per quality point$0.068
Est. monthly (1M tokens/day)$82.50
Qwen3 Max Thinking
Input cost$0.78/M tokens
Output cost$3.90/M tokens
Cost per quality point$0.069
Est. monthly (1M tokens/day)$70.20

Muse Spark 1.2 offers 15% better value per quality point. At 1M tokens/day, you'd spend $70.20/month with Qwen3 Max Thinking vs $82.50/month with Muse Spark 1.2 - a $12.30 monthly difference.

Latency & Speed
Muse Spark 1.2Faster
Speed score0/100
Qwen3 Max Thinking
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

Muse Spark 1.2

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3 Max Thinking also offers lower per-token costs for high-volume support

Muse Spark 1.2

Long document analysis

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

Muse Spark 1.2

Batch data extraction

Lower output pricing ($3.90/M) reduces costs when processing thousands of records daily

Qwen3 Max Thinking

Creative writing & content

Higher overall composite score (81/100) correlates with better nuance, coherence, and style in long-form content

Muse Spark 1.2

Image understanding & OCR

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

Muse Spark 1.2
Which Should You Choose?
Our recommendation:
Muse Spark 1.2

Muse Spark 1.2 clearly outperforms Qwen3 Max Thinking with a significant 12.700000000000003-point lead. For most general use cases, Muse Spark 1.2 is the stronger choice. However, Qwen3 Max Thinking may still excel in niche scenarios.

Muse Spark 1.2
Recommended

by meta

  • 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 Alibaba

  • Choose for Cost - 15% lower pricing; better value at scale
Capability Comparison
CapabilityMuse Spark 1.2Qwen3 Max Thinking
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)

Muse Spark 1.2

meta

$7.35
estimated monthly cost

Qwen3 Max Thinking

Alibaba

Best Value
$6.08
estimated monthly cost

Qwen3 Max Thinking saves you $1.27/month

That's 17% cheaper than Muse Spark 1.2 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
ParameterMuse Spark 1.2Qwen3 Max Thinking
Context Window1.0M262K
Max Output Tokens943,71865,536
Open SourceNoNo
CreatedAug 5, 2026Feb 9, 2026
Last updated: 9m ago

相关对比

Muse Spark 1.2 vs Qwen3 Max Thinking (2026) | LM Market Cap