GPT-6 Luna (batch) vs Qwen3 235B A22B Thinking 2507
| Signal | GPT-6 Luna (batch) | Delta | Qwen3 235B A22B Thinking 2507 |
|---|---|---|---|
Capabilities | 100 | +33 | |
Pricing | 100 | +2 | |
Context window size | 96 | +14 | |
Recency | 100 | +45 | |
Output Capacity | 82 | +1 | |
Benchmarks | 0 | -64 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
40
current score
Qwen3 235B A22B Thinking 2507
right now
65.3
current score
GPT-6 Luna (batch)
OpenAI
Qwen3 235B A22B Thinking 2507
Alibaba
GPT-6 Luna (batch) saves you $120.50/month
That's $1446.00/year compared to Qwen3 235B A22B Thinking 2507 at your current usage level of 100K calls/month.
| Metric | GPT-6 Luna (batch) | Qwen3 235B A22B Thinking 2507 | Winner |
|---|---|---|---|
| Overall Score | 40 | 65 | Qwen3 235B A22B Thinking 2507 |
| Rank | #238 | #195 | Qwen3 235B A22B Thinking 2507 |
| Quality Rank | #238 | #195 | Qwen3 235B A22B Thinking 2507 |
| Adoption Rank | #238 | #195 | Qwen3 235B A22B Thinking 2507 |
| Parameters | -- | 235B | -- |
| Context Window | 1050K | 131K | GPT-6 Luna (batch) |
| Pricing | $0.05/$0.25/M | $0.23/$2.30/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | GPT-6 Luna (batch) |
| Pricing | 100 | 98 | GPT-6 Luna (batch) |
| Context window size | 96 | 81 | GPT-6 Luna (batch) |
| Recency | 100 | 56 | GPT-6 Luna (batch) |
| Output Capacity | 82 | 81 | GPT-6 Luna (batch) |
| Benchmarks | -- | 64 | Qwen3 235B A22B Thinking 2507 |
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.
Scores 40/100 (rank #238), placing it in the top 18% of all 290 models tracked.
Scores 65/100 (rank #195), placing it in the top 33% of all 290 models tracked.
Qwen3 235B A22B Thinking 2507 has a 25-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Choose GPT-6 Luna (batch) when you need:
- High-volume production workloads where API costs must be minimized
- 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 Qwen3 235B A22B Thinking 2507 when you need:
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
GPT-6 Luna (batch) offers 88% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with GPT-6 Luna (batch) vs $37.95/month with Qwen3 235B A22B Thinking 2507 - a $33.45 monthly difference.
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.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GPT-6 Luna (batch) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.25/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (65/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen3 235B A22B Thinking 2507 clearly outperforms GPT-6 Luna (batch) with a significant 25.299999999999997-point lead. For most general use cases, Qwen3 235B A22B Thinking 2507 is the stronger choice. However, GPT-6 Luna (batch) may still excel in niche scenarios.
By Use Case
Best for Quality
GPT-6 Luna (batch)
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-6 Luna (batch)
88% lower pricing; better value at scale
Best for Reliability
GPT-6 Luna (batch)
Higher uptime and faster response speeds
Best for Prototyping
GPT-6 Luna (batch)
Stronger community support and better developer experience
Best for Production
GPT-6 Luna (batch)
Wider enterprise adoption and proven at scale
by OpenAI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Cost - 88% 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
| Capability | GPT-6 Luna (batch) | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
GPT-6 Luna (batch)
OpenAI
Qwen3 235B A22B Thinking 2507
Alibaba
GPT-6 Luna (batch) saves you $2.78/month
That's 88% cheaper than Qwen3 235B A22B Thinking 2507 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.
| Parameter | GPT-6 Luna (batch) | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Context Window | 1.1M | 131K |
| Max Output Tokens | 128,000 | 117,964 |
| Open Source | No | Yes |
| Created | Sep 22, 2026 | Jul 25, 2025 |