Ling 3.0 Flash VL vs Qwen3.8 Flash
Too close to call on our weighted score (Ling 3.0 Flash VL 76, Qwen3.8 Flash 74). The right pick depends on what you value most.
inclusionAI
Ling 3.0 Flash VL
76/100- ECI—
- Price$0.06 / $0.18
- Context262K
Alibaba (Qwen)
Qwen3.8 Flash
74/100- ECI—
- Price$0.15 / $0.47
- Context1M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Ling 3.0 Flash VL 76/100, Qwen3.8 Flash 74/100), so choose by what matters most for your work: Ling 3.0 Flash VL on price and Qwen3.8 Flash for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceLing 3.0 Flash VLLing 3.0 Flash VL $0.09 · Qwen3.8 Flash $0.23 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 FlashQwen3.8 Flash 1,000,000 · Ling 3.0 Flash VL 262,144 tokens
- Widest inputsSame inputsLing 3.0 Flash VL: Text, Images, Video · Qwen3.8 Flash: Text, Images, Video
- Self-hostingLing 3.0 Flash VLPublishes downloadable weights (MIT)
| Measure | Weight | Ling 3.0 Flash VL | Qwen3.8 Flash |
|---|---|---|---|
| Price | 50% | 95 | 77 |
| Inputs & features | 30% | 70 | 80 |
| Context window | 20% | 37 | 60 |
| Overall | 100% | 76/100 | 74/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.06 (best) | $0.15 |
| Output | $0.18 (best) | $0.47 |
| Cached input | — | $0.016 |
| Blended (3:1) | $0.09 (best) | $0.23 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 7 providers | Official Alibaba API |
| Limits | ||
| Context window | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | Yes | Yes |
| Reasoning | Yes | Yeslow · medium · xhigh |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenMIT | Proprietary |
| API model ID | — | qwen3.8-flash |
| API providers | 7 | 28 (best) |
| Released | Sep 10, 2026 | Aug 26, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Ling 3.0 Flash VL$0.96
Qwen3.8 Flash$2.44
Which should you choose?
Which is better: Ling 3.0 Flash VL or Qwen3.8 Flash?
It is close. Our weighted score puts them within 2 points (Ling 3.0 Flash VL 76/100, Qwen3.8 Flash 74/100), so choose by what matters most for your work: Ling 3.0 Flash VL on price and Qwen3.8 Flash for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Ling 3.0 Flash VL or Qwen3.8 Flash?
Ling 3.0 Flash VL is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). Qwen3.8 Flash costs $0.15 input / $0.47 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.09 per million tokens for Ling 3.0 Flash VL versus $0.23 for Qwen3.8 Flash (2.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Ling 3.0 Flash VL has not been scored yet and Qwen3.8 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ling 3.0 Flash VL and Qwen3.8 Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.8 Flash has the largest context window at 1,000,000 tokens, against 262,144 for Ling 3.0 Flash VL. Maximum output per response: Ling 3.0 Flash VL up to 32,768, Qwen3.8 Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Ling 3.0 Flash VL accepts text, images and video; Qwen3.8 Flash accepts text, images and video. They handle the same number of input types.
Are any of these open source?
Ling 3.0 Flash VL publishes its weights (MIT) and can be self-hosted; Qwen3.8 Flash is proprietary.
Which is newer?
Ling 3.0 Flash VL is the newest, released Sep 10, 2026. Qwen3.8 Flash came out Aug 26, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.