multimodal model comparison
GPT-5.6 Luna vs Qwen3.8-Omni-Flash
GPT-5.6 Luna and Qwen3.8-Omni-Flash are both current multimodal models, from OpenAI and Alibaba Qwen. Qwen3.8-Omni-Flash is 25% cheaper per 1M input tokens than GPT-5.6 Luna, $0.15 vs $0.20. GPT-5.6 Luna has the larger context window, 1,050,000 vs 1,000,000 tokens.
Data verified October 12, 2026 · Dataset 2026-10-12
Side by side
Standard-tier prices in effect today. The better value in each row is highlighted.
| Fact | GPT-5.6 Luna | Qwen3.8-Omni-Flash |
|---|---|---|
| Price per 1M input tokens | $0.20 | $0.15 (better) |
| Price per 1M output tokens | $1.20 | $0.47 (better) |
| Cost of 10M input and 2M output tokens | $4.40 | $2.44 (better) |
| Arena Text | 1452 Elo (#29 of 39) | Not measured |
| GPQA Diamond | 91.6% (#19 of 37) | Not measured |
| FrontierMath Tiers 1-3 (v2) | 82.1% (#12 of 37) | Not measured |
| SimpleQA Verified | 41% (#26 of 34) | Not measured |
| Provider | OpenAI | Alibaba Qwen |
| Release date | July 9, 2026 | September 20, 2026 |
| Access | API only | API only |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 131,072 tokens |
| Input | text, image | text, image, audio, video |
| Output | text | text |
When to choose each
GPT-5.6 Luna
Best for
- High-volume API evaluation with published low token prices
- Subagents and batch reasoning where cost per call dominates
Watch out for
- Not in the pinned LiveBench snapshot; its independent scores here come from Epoch AI's own GPQA Diamond, FrontierMath and SimpleQA Verified runs
Qwen3.8-Omni-Flash
Best for
- Long audio and video understanding at low cost
- Agent pipelines that must reason over meetings, calls or recorded media
Watch out for
- Output is text only; for spoken replies Alibaba lists a separate realtime variant
- Alibaba's comparisons with Gemini 3.8 Flash are self-reported and have not been reproduced independently here
- The release date is the Alibaba Cloud announcement date, 2026-09-20
GPT-5.6 Luna vs Qwen3.8-Omni-Flash FAQ
Which is cheaper, GPT-5.6 Luna or Qwen3.8-Omni-Flash?
Qwen3.8-Omni-Flash is 25% cheaper per 1M input tokens than GPT-5.6 Luna, $0.15 vs $0.20. For 10M input and 2M output tokens, GPT-5.6 Luna costs $4.40 and Qwen3.8-Omni-Flash $2.44 at standard rates.
Which has the larger context window, GPT-5.6 Luna or Qwen3.8-Omni-Flash?
GPT-5.6 Luna has the larger context window, 1,050,000 vs 1,000,000 tokens.
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Production evaluation
Choosing between GPT-5.6 Luna and Qwen3.8-Omni-Flash?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty