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GPT-6 Luna vs Qwen3.8 Max Prime

GPT-6 Luna

OpenAI

40#242
vs
Qwen3.8 Max Prime

Alibaba

40#236
Signal-by-Signal Comparison
SignalGPT-6 LunaDeltaQwen3.8 Max Prime
Capabilities
100
+17
83
Pricing
100
+12
88
Context window size
96
+0
95
Recency
100
--
100
Output Capacity
82
0
82
Overall Result
3 wins
of 5
1 wins
GPT-6 Luna wins 3 of 5 signals

Score History Unavailable

Not enough historical data to show a comparison chart. Score history is recorded weekly and will be available after at least two data points are collected.

40

GPT-6 Luna

vs

40

Qwen3.8 Max Prime

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

GPT-6 Luna

OpenAI

Best Value
Per request$0.000350
Daily$1.17
Monthly$35.00
Annual$420.00

Qwen3.8 Max Prime

Alibaba

Per request$0.010000
Daily$33.33
Monthly$1000.00
Annual$12000.00

GPT-6 Luna saves you $965.00/month

That's $11580.00/year compared to Qwen3.8 Max Prime at your current usage level of 100K calls/month.

97% cheaper
Choose GPT-6 Luna for cost optimization

GPT-6 Luna pricing:
Input:$0.10/M tokens
Output:$0.50/M tokens
Qwen3.8 Max Prime pricing:
Input:$4.00/M tokens
Output:$12.00/M tokens
Tie
GPT-6 Luna

OpenAI

40

Composite Score

Tie
Qwen3.8 Max Prime

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricGPT-6 LunaQwen3.8 Max PrimeWinner
Overall Score
40
40
--
Rank#242#236
Qwen3.8 Max Prime
Quality Rank#242#236
Qwen3.8 Max Prime
Adoption Rank#242#236
Qwen3.8 Max Prime
Parameters------
Context Window1050K1000K
GPT-6 Luna
Pricing$0.10/$0.50/M$4.00/$12.00/M--
Signal Scores
Capabilities
100
83
GPT-6 Luna
Pricing
100
88
GPT-6 Luna
Context window size
96
95
GPT-6 Luna
Recency
100
100
GPT-6 Luna
Output Capacity
82
82
Qwen3.8 Max Prime
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.

GPT-6 LunaEntry Level

Scores 40/100 (rank #242), placing it in the top 17% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.8 Max PrimeEntry Level

Scores 40/100 (rank #236), placing it in the top 19% 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 GPT-6 Luna when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Qwen3.8 Max Prime when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
GPT-6 LunaBest Value
Input cost$0.10/M tokens
Output cost$0.50/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.00
Qwen3.8 Max Prime
Input cost$4.00/M tokens
Output cost$12.00/M tokens
Cost per quality point$0.400
Est. monthly (1M tokens/day)$240.00

GPT-6 Luna offers 96% better value per quality point. At 1M tokens/day, you'd spend $9.00/month with GPT-6 Luna vs $240.00/month with Qwen3.8 Max Prime - a $231.00 monthly difference.

Latency & Speed
GPT-6 LunaFaster
Speed score0/100
Qwen3.8 Max Prime
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

GPT-6 Luna

Customer support chatbot

Suitable for user-facing chat with competitive response times. GPT-6 Luna also offers lower per-token costs for high-volume support

GPT-6 Luna

Long document analysis

Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass

GPT-6 Luna

Batch data extraction

Lower output pricing ($0.50/M) reduces costs when processing thousands of records daily

GPT-6 Luna

Creative writing & content

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

GPT-6 Luna

Image understanding & OCR

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

GPT-6 Luna
Which Should You Choose?
Our recommendation:
GPT-6 Luna

GPT-6 Luna and Qwen3.8 Max Prime 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.

GPT-6 Luna
Recommended

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 96% lower pricing; better value at scale
  • 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

Consider for specialized use cases.

Capability Comparison
CapabilityGPT-6 LunaQwen3.8 Max Prime
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-6 Luna

OpenAI

Best Value
$0.7800
estimated monthly cost

Qwen3.8 Max Prime

Alibaba

$21.60
estimated monthly cost

GPT-6 Luna saves you $20.82/month

That's 96% cheaper than Qwen3.8 Max Prime 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
ParameterGPT-6 LunaQwen3.8 Max Prime
Context Window1.1M1M
Max Output Tokens128,000131,072
Open SourceNoNo
CreatedSep 22, 2026Sep 23, 2026
Last updated: 25m ago

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