GPT-6 Luna (batch) vs Qwen3 235B A22B Instruct 2507
| Signal | GPT-6 Luna (batch) | Delta | Qwen3 235B A22B Instruct 2507 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Pricing | 100 | +0 | |
Context window size | 96 | +10 | |
Recency | 100 | +45 | |
Output Capacity | 82 | -4 | |
Benchmarks | 0 | -64 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
40
current score
Qwen3 235B A22B Instruct 2507
right now
64.7
current score
GPT-6 Luna (batch)
OpenAI
Qwen3 235B A22B Instruct 2507
Alibaba
GPT-6 Luna (batch) saves you $8.75/month
That's $105.00/year compared to Qwen3 235B A22B Instruct 2507 at your current usage level of 100K calls/month.
| Metric | GPT-6 Luna (batch) | Qwen3 235B A22B Instruct 2507 | Winner |
|---|---|---|---|
| Overall Score | 40 | 65 | Qwen3 235B A22B Instruct 2507 |
| Rank | #238 | #198 | Qwen3 235B A22B Instruct 2507 |
| Quality Rank | #238 | #198 | Qwen3 235B A22B Instruct 2507 |
| Adoption Rank | #238 | #198 | Qwen3 235B A22B Instruct 2507 |
| Parameters | -- | 235B | -- |
| Context Window | 1050K | 262K | GPT-6 Luna (batch) |
| Pricing | $0.05/$0.25/M | $0.09/$0.35/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-6 Luna (batch) |
| Pricing | 100 | 100 | GPT-6 Luna (batch) |
| Context window size | 96 | 86 | GPT-6 Luna (batch) |
| Recency | 100 | 55 | GPT-6 Luna (batch) |
| Output Capacity | 82 | 86 | Qwen3 235B A22B Instruct 2507 |
| Benchmarks | -- | 64 | Qwen3 235B A22B Instruct 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 #198), placing it in the top 32% of all 290 models tracked.
Qwen3 235B A22B Instruct 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:
- 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 Instruct 2507 when you need:
- Self-hosted deployments where you need full control over the model
Qwen3 235B A22B Instruct 2507 offers 31% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with GPT-6 Luna (batch) vs $6.56/month with Qwen3 235B A22B Instruct 2507 - a $2.06 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 Instruct 2507 clearly outperforms GPT-6 Luna (batch) with a significant 24.700000000000003-point lead. For most general use cases, Qwen3 235B A22B Instruct 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)
31% 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 - 31% 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 Instruct 2507 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
GPT-6 Luna (batch)
OpenAI
Qwen3 235B A22B Instruct 2507
Alibaba
GPT-6 Luna (batch) saves you $0.1875/month
That's 32% cheaper than Qwen3 235B A22B Instruct 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 Instruct 2507 |
|---|---|---|
| Context Window | 1.1M | 262K |
| Max Output Tokens | 128,000 | 235,929 |
| Open Source | No | Yes |
| Created | Sep 22, 2026 | Jul 21, 2025 |