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GPT-6 Luna Pro (batch) vs Qwen2.5 7B Instruct

Signal-by-Signal Comparison
SignalGPT-6 Luna Pro (batch)DeltaQwen2.5 7B Instruct
Capabilities
100
+50
50
Pricing
100
--
100
Context window size
96
+24
72
Recency
100
+96
4
Output Capacity
82
+10
72
Benchmarks
0
-39
39
Overall Result
4 wins
of 6
1 wins
GPT-6 Luna Pro (batch) wins 4 of 6 signals

Score History

Score History (32 data points)
GPT-6 Luna Pro (batch)Qwen2.5 7B Instruct
GPT-6 Luna Pro (batch)

40

current score

Leader

GPT-6 Luna Pro (batch)

right now

Qwen2.5 7B Instruct

38.1

current score

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

GPT-6 Luna Pro (batch)

OpenAI

Best Value
Per request$0.000175
Daily$0.58
Monthly$17.50
Annual$210.00

Qwen2.5 7B Instruct

Alibaba

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

GPT-6 Luna Pro (batch) saves you $2.50/month

That's $30.00/year compared to Qwen2.5 7B Instruct at your current usage level of 100K calls/month.

13% cheaper
Choose GPT-6 Luna Pro (batch) for cost optimization

GPT-6 Luna Pro (batch) pricing:
Input:$0.05/M tokens
Output:$0.25/M tokens
Qwen2.5 7B Instruct pricing:
Input:$0.10/M tokens
Output:$0.20/M tokens
Winner
GPT-6 Luna Pro (batch)

OpenAI

40

Composite Score

Qwen2.5 7B Instruct

Alibaba

38

Composite Score

Signal-by-Signal Comparison
MetricGPT-6 Luna Pro (batch)Qwen2.5 7B InstructWinner
Overall Score
40
38
GPT-6 Luna Pro (batch)
Rank#242#423
GPT-6 Luna Pro (batch)
Quality Rank#242#423
GPT-6 Luna Pro (batch)
Adoption Rank#242#423
GPT-6 Luna Pro (batch)
Parameters--7B--
Context Window1050K33K
GPT-6 Luna Pro (batch)
Pricing$0.05/$0.25/M$0.10/$0.20/M--
Signal Scores
Capabilities
100
50
GPT-6 Luna Pro (batch)
Pricing
100
100
GPT-6 Luna Pro (batch)
Context window size
96
72
GPT-6 Luna Pro (batch)
Recency
100
4
GPT-6 Luna Pro (batch)
Output Capacity
82
72
GPT-6 Luna Pro (batch)
Benchmarks--
39
Qwen2.5 7B Instruct
Benchmark Head-to-Head(4 benchmarks)
GPT-6 Luna: 0Qwen2.5 7B: 0
GPT-6 Luna
Qwen2.5 7B
Normalized 0-100%
MMLU-Pro
-36.52%
IFEval
-75.85%
BBH
-34.89%
BigCodeBench
-37.6%
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 Luna Pro (batch)Entry 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
Qwen2.5 7B InstructEntry Level

Scores 38/100 (rank #423), placing it in the top -46% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 2-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 Pro (batch) when you need:

  • Processing long documents or large codebases (1050K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving

Choose Qwen2.5 7B Instruct when you need:

  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
GPT-6 Luna Pro (batch)Best Value
Input cost$0.05/M tokens
Output cost$0.25/M tokens
Cost per quality point$0.007
Est. monthly (1M tokens/day)$4.50
Qwen2.5 7B Instruct
Input cost$0.10/M tokens
Output cost$0.20/M tokens
Cost per quality point$0.008
Est. monthly (1M tokens/day)$4.50

Both models are priced similarly, so the decision comes down to quality and features rather than cost.

Latency & Speed
GPT-6 Luna Pro (batch)Faster
Speed score0/100
Qwen2.5 7B Instruct
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 Pro (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen2.5 7B Instruct also offers lower per-token costs for high-volume support

GPT-6 Luna Pro (batch)

Long document analysis

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

GPT-6 Luna Pro (batch)

Batch data extraction

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

Qwen2.5 7B Instruct

Creative writing & content

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

GPT-6 Luna Pro (batch)

Image understanding & OCR

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

GPT-6 Luna Pro (batch)
Which Should You Choose?
Our recommendation:
GPT-6 Luna Pro (batch)

GPT-6 Luna Pro (batch) and Qwen2.5 7B Instruct are extremely close in overall performance (only 1.8999999999999986 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 0% 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 Luna Pro (batch)Qwen2.5 7B Instruct
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoningdiffers
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-6 Luna Pro (batch)

OpenAI

Best Value
$0.3900
estimated monthly cost

Qwen2.5 7B Instruct

Alibaba

$0.4200
estimated monthly cost

GPT-6 Luna Pro (batch) saves you $0.0300/month

That's 7% cheaper than Qwen2.5 7B Instruct 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 Luna Pro (batch)Qwen2.5 7B Instruct
Context Window1.1M33K
Max Output Tokens128,00029,491
Open SourceNoYes
CreatedSep 22, 2026Oct 16, 2024
Last updated: 20m ago

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GPT-6 Luna Pro (batch) vs Qwen2.5 7B Instruct (2026) | LM Market Cap