GPT-6 Luna Pro (batch) vs SWE-1.5
| Signal | GPT-6 Luna Pro (batch) | Delta | SWE-1.5 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Pricing | 100 | 0 | |
Context window size | 96 | +96 | |
Recency | 100 | +38 | |
Output Capacity | 82 | +62 | |
| Overall Result | 4 wins | of 5 | 1 wins |
Score History
40
current score
GPT-6 Luna Pro (batch)
right now
36.1
current score
GPT-6 Luna Pro (batch)
OpenAI
SWE-1.5
Windsurf
SWE-1.5 saves you $17.50/month
That's $210.00/year compared to GPT-6 Luna Pro (batch) at your current usage level of 100K calls/month.
| Metric | GPT-6 Luna Pro (batch) | SWE-1.5 | Winner |
|---|---|---|---|
| Overall Score | 40 | 36 | GPT-6 Luna Pro (batch) |
| Rank | #236 | #420 | GPT-6 Luna Pro (batch) |
| Quality Rank | #236 | #420 | GPT-6 Luna Pro (batch) |
| Adoption Rank | #236 | #420 | GPT-6 Luna Pro (batch) |
| Parameters | -- | -- | -- |
| Context Window | 1050K | -- | -- |
| Pricing | $0.05/$0.25/M | Free | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-6 Luna Pro (batch) |
| Pricing | 100 | 100 | SWE-1.5 |
| Context window size | 96 | 0 | GPT-6 Luna Pro (batch) |
| Recency | 100 | 62 | GPT-6 Luna Pro (batch) |
| Output Capacity | 82 | 20 | GPT-6 Luna Pro (batch) |
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 #236), placing it in the top 19% of all 290 models tracked.
Scores 36/100 (rank #420), placing it in the top -44% of all 290 models tracked.
With only a 4-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.
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 SWE-1.5 when you need:
- High-volume production workloads where API costs must be minimized
- Step-by-step reasoning and chain-of-thought problem solving
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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. SWE-1.5 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 ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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
GPT-6 Luna Pro (batch) has a moderate advantage with a 3.8999999999999986-point lead in composite score. It wins on more signal dimensions, but SWE-1.5 has specific strengths that could make it the better choice for certain workflows.
By Use Case
Best for Quality
GPT-6 Luna Pro (batch)
Marginally better benchmark scores; both are excellent
Best for Cost
SWE-1.5
100% lower pricing; better value at scale
Best for Reliability
GPT-6 Luna Pro (batch)
Higher uptime and faster response speeds
Best for Prototyping
GPT-6 Luna Pro (batch)
Stronger community support and better developer experience
Best for Production
GPT-6 Luna Pro (batch)
Wider enterprise adoption and proven at scale
by OpenAI
- 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
| Capability | GPT-6 Luna Pro (batch) | SWE-1.5 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
GPT-6 Luna Pro (batch)
OpenAI
SWE-1.5
Windsurf
SWE-1.5 saves you $0.3900/month
That's 100% cheaper than GPT-6 Luna Pro (batch) 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 Pro (batch) | SWE-1.5 |
|---|---|---|
| Context Window | 1.1M | -- |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | No |
| Created | Sep 22, 2026 | Sep 1, 2025 |