Ling 3.0 Flash vs Qwen3.8 Flash vs Nemotron 3.5 Lightning 30B A3B
Qwen3.8 Flash comes out ahead, 74 to 68 and 65 on our weighted score, though Ling 3.0 Flash is 2.6× cheaper per token.
inclusionAILing 3.0 Flash
65/100- ECI—
- Price$0.06 / $0.18
- Context262K
- Our pick
Alibaba (Qwen)Qwen3.8 Flash
74/100- ECI—
- Price$0.15 / $0.47
- Context1M
NVIDIANemotron 3.5 Lightning 30B A3B
68/100- ECI—
- Price$0.055 / $0.20
- Context262K
Qwen3.8 Flash is our pick
Qwen3.8 Flash is the better all-round choice, scoring 74/100 against Nemotron 3.5 Lightning 30B A3B (68) and Ling 3.0 Flash (65). It leads on inputs & features and context window. 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 FlashLing 3.0 Flash $0.09 · Nemotron 3.5 Lightning 30B A3B $0.091 · Qwen3.8 Flash $0.23 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 FlashQwen3.8 Flash 1,000,000 · Ling 3.0 Flash 262,144 · Nemotron 3.5 Lightning 30B A3B 262,144 tokens
- Widest inputsQwen3.8 FlashLing 3.0 Flash: Text · Qwen3.8 Flash: Text, Images, Video · Nemotron 3.5 Lightning 30B A3B: Text
- Self-hostingLing 3.0 Flash and Nemotron 3.5 Lightning 30B A3BPublishes downloadable weights (MIT)
| Measure | Weight | Ling 3.0 Flash | Qwen3.8 Flash | Nemotron 3.5 Lightning 30B A3B |
|---|---|---|---|---|
| Price | 50% | 95 | 77 | 95 |
| Inputs & features | 30% | 35 | 80 | 45 |
| Context window | 20% | 37 | 60 | 37 |
| Overall | 100% | 65/100 | 74/100 | 68/100 |
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 | Ling 3.0 FlashinclusionAI | Qwen3.8 FlashAlibaba (Qwen) | Nemotron 3.5 Lightning 30B A3BNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.06 | $0.15 | $0.055 (best) |
| Output | $0.18 (best) | $0.47 | $0.20 |
| Cached input | — | $0.016 | — |
| Blended (3:1) | $0.09 (best) | $0.23 | $0.091 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Official Alibaba API | Median of 10 providers |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 262,144 tokens |
| Max output | 32,768 tokens | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yeslow · medium · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenMIT | Proprietary | Open |
| API model ID | — | qwen3.8-flash | nvidia/nemotron-3.5-lightning-30b-a3b |
| API providers | 9 | 28 (best) | 15 |
| Released | Jul 23, 2026 | Aug 26, 2026 | Aug 11, 2026 |
| Knowledge cutoff | — | — | Sep 2025 |
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$0.96
- Qwen3.8 Flash$2.44
- Nemotron 3.5 Lightning 30B A3B$0.95
Which should you choose?
Which is better: Ling 3.0 Flash, Qwen3.8 Flash or Nemotron 3.5 Lightning 30B A3B?
Qwen3.8 Flash is the better all-round choice, scoring 74/100 against Nemotron 3.5 Lightning 30B A3B (68) and Ling 3.0 Flash (65). It leads on inputs & features and context window. 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, Qwen3.8 Flash or Nemotron 3.5 Lightning 30B A3B?
Ling 3.0 Flash is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). Nemotron 3.5 Lightning 30B A3B costs $0.055 input / $0.20 output per million tokens (median across 10 API providers; free on Nvidia); 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 versus $0.091 for Nemotron 3.5 Lightning 30B A3B (1× as much) and $0.23 for Qwen3.8 Flash (2.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Ling 3.0 Flash has not been scored yet, Qwen3.8 Flash has not been scored yet and Nemotron 3.5 Lightning 30B A3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ling 3.0 Flash, Qwen3.8 Flash and Nemotron 3.5 Lightning 30B A3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 and 262,144 for Nemotron 3.5 Lightning 30B A3B. Maximum output per response: Ling 3.0 Flash up to 32,768, Qwen3.8 Flash up to 131,072, Nemotron 3.5 Lightning 30B A3B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Ling 3.0 Flash accepts text; Qwen3.8 Flash accepts text, images and video; Nemotron 3.5 Lightning 30B A3B accepts text. Qwen3.8 Flash handles the widest range of inputs.
Are any of these open source?
Ling 3.0 Flash and Nemotron 3.5 Lightning 30B A3B publishes its weights (MIT) and can be self-hosted; Qwen3.8 Flash is proprietary.
Which is newer?
Qwen3.8 Flash is the newest, released Aug 26, 2026. Nemotron 3.5 Lightning 30B A3B came out Aug 11, 2026; Ling 3.0 Flash came out Jul 23, 2026. Knowledge cutoff: Nemotron 3.5 Lightning 30B A3B Sep 2025.
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.
