Compare / head-to-head
GPT-5.6 LunavsStep 3.7 Flash
GPT-5.6 Luna and Step 3.7 Flash do not yet share a public benchmark, so quality cannot be compared apples-to-apples. GPT-5.6 Luna has the larger context window (1.1M tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
0
no overlap yet
Cheaper per token
—
list price, input + output
Larger context
GPT-5.6 Luna
1.1M tokens
Provider uptime (30d)
95.1662% · —
OpenAI · StepFun
GPT-5.6 Luna
OpenAI · released 2026-07-09
textvision
Step 3.7 Flash
StepFun · released 2026-05-29
textvision
- Context
- 256K
- Max out
- —
- Input /1M
- —
- Output /1M
- —
- Cached /1M
- —
- Scores
- 19 · 6 core
Quality
Benchmark matrix
0 shared · 7 only GPT-5.6 Luna · 19 only Step 3.7 Flash| Benchmark | GPT-5.6 Luna | Step 3.7 Flash | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 0 | ||||
| No public benchmark is reported for both models yet. | ||||
| Only GPT-5.6 Luna reports · 7 | ||||
| GPQA Diamond | 92.3% ↗ | not reported | — | — |
| DeepSWE v1.1 | 67.2% ↗ | not reported | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | 61% ↗epoch | not reported | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | 82.1% ↗epoch | not reported | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | 98.3% ↗epoch | not reported | — | — |
| SimpleQA Verified | 41% ↗epoch | not reported | — | — |
| SWE-Bench Pro | 62.7% ↗ | not reported | — | — |
| Only Step 3.7 Flash reports · 19 | ||||
| SWE-bench Verified | not reported | 76.5% ↗ | — | — |
| AIME 2026 | not reported | 95% ↗matharena ⚠ | — | — |
| AA-LCR | not reported | 63.9% ↗ | — | — |
| BrowseComp | not reported | 75.8% ↗ | — | — |
| ClawEval v1.1 | not reported | 67.1% ↗ | — | — |
| DeepSearchQA Accuracy | not reported | 81.7% ↗ | — | — |
| DeepSearchQA F1 | not reported | 92.8% ↗ | — | — |
| GDPval-Stirrup | not reported | 1415.8 ↗ | — | — |
| GDPval-Stirrup Intelligence Index | not reported | 45.8 ↗ | — | — |
| HLE (with tools, text-only) | not reported | 49.7% ↗ | — | — |
| HLE (with tools) | not reported | 47.2% ↗ | — | — |
| ResearchRubrics | not reported | 71.7% ↗ | — | — |
| SimpleVQA (with tools) | not reported | 79.2% ↗ | — | — |
| SWE-bench Multilingual | not reported | 72.4% ↗ | — | — |
| SWE-bench Pro | not reported | 56.3% ↗ | — | — |
| Terminal-Bench 2.1 | not reported | 59.6% ↗ | — | — |
| Toolathlon | not reported | 49.5% ↗ | — | — |
| V* (with Python) | not reported | 95.3% ↗ | — | — |
| WorldVQA (with visual search) | not reported | 58.1% ↗ | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GPT-5.6 Luna minus Step 3.7 Flash in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GPT-5.6 Luna | Step 3.7 Flash | Edge |
|---|---|---|---|
| Context window | 1.1M tokens | 256K tokens | GPT-5.6 Luna |
| Max output | 128K tokens | — | — |
| Input price / 1M | $0.2 ↗ | — | — |
| Output price / 1M | $1.2 ↗ | — | — |
| Cached input / 1M | $0.02 ↗ | — | — |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $1.4 | — | — |
| Modalities | text · vision | text · vision | Tie |
| Released | 2026-07-09 | 2026-05-29 | — |
| Cited benchmark scores | 8 | 19 | — |
Reliability
Provider status
Last 60 days · refreshed daily on this page · live on /statusMore matchups
GPT-5.6 Luna vs …
Models sharing the most benchmarksMore matchups
Step 3.7 Flash vs …
Models sharing the most benchmarksBuilt by Respan
Which one wins on your data?
Public benchmarks are a starting point. Run GPT-5.6 Luna and Step 3.7 Flash on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.