Ling 3.0 Flash vs Ling 3.0 Flash VL vs Nemotron 3.5 Lightning 30B A3B
Ling 3.0 Flash VL comes out ahead, 76 to 68 and 65 on our weighted score.
inclusionAILing 3.0 Flash
65/100- ECI—
- Price$0.06 / $0.18
- Context262K
- Our pickinclusionAI
Ling 3.0 Flash VL
76/100- ECI—
- Price$0.06 / $0.18
- Context262K
NVIDIANemotron 3.5 Lightning 30B A3B
68/100- ECI—
- Price$0.055 / $0.20
- Context262K
Ling 3.0 Flash VL is our pick
Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Nemotron 3.5 Lightning 30B A3B (68) and Ling 3.0 Flash (65). It leads on inputs & features. 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 and Ling 3.0 Flash VLLing 3.0 Flash $0.09 · Ling 3.0 Flash VL $0.09 · Nemotron 3.5 Lightning 30B A3B $0.091 per 1M tokens (3:1 blend)
- Longest contextAbout the sameLing 3.0 Flash 262,144 · Ling 3.0 Flash VL 262,144 · Nemotron 3.5 Lightning 30B A3B 262,144 tokens
- Widest inputsLing 3.0 Flash VLLing 3.0 Flash: Text · Ling 3.0 Flash VL: Text, Images, Video · Nemotron 3.5 Lightning 30B A3B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ling 3.0 Flash | Ling 3.0 Flash VL | Nemotron 3.5 Lightning 30B A3B |
|---|---|---|---|---|
| Price | 50% | 95 | 95 | 95 |
| Inputs & features | 30% | 35 | 70 | 45 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 65/100 | 76/100 | 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 | Ling 3.0 Flash VLinclusionAI | Nemotron 3.5 Lightning 30B A3BNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.06 | $0.06 | $0.055 (best) |
| Output | $0.18 (best) | $0.18 (best) | $0.20 |
| Cached input | — | — | — |
| Blended (3:1) | $0.09 (best) | $0.09 (best) | $0.091 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 7 providers | Median of 10 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 32,768 tokens | 32,768 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 | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenMIT | OpenMIT | Open |
| API model ID | — | — | nvidia/nemotron-3.5-lightning-30b-a3b |
| API providers | 9 | 7 | 15 (best) |
| Released | Jul 23, 2026 | Sep 10, 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
- Ling 3.0 Flash VL$0.96
- Nemotron 3.5 Lightning 30B A3B$0.95
Which should you choose?
Which is better: Ling 3.0 Flash, Ling 3.0 Flash VL or Nemotron 3.5 Lightning 30B A3B?
Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Nemotron 3.5 Lightning 30B A3B (68) and Ling 3.0 Flash (65). It leads on inputs & features. 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, Ling 3.0 Flash VL 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). Ling 3.0 Flash VL costs $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). 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 $0.09 for Ling 3.0 Flash VL (1× as much) and $0.091 for Nemotron 3.5 Lightning 30B A3B (1× 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, Ling 3.0 Flash VL 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, Ling 3.0 Flash VL 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?
Ling 3.0 Flash, Ling 3.0 Flash VL and Nemotron 3.5 Lightning 30B A3B share the same 262,144-token context window. Maximum output per response: Ling 3.0 Flash up to 32,768, Ling 3.0 Flash VL up to 32,768, 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; Ling 3.0 Flash VL accepts text, images and video; Nemotron 3.5 Lightning 30B A3B accepts text. Ling 3.0 Flash VL handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (MIT), so you can self-host them.
Which is newer?
Ling 3.0 Flash VL is the newest, released Sep 10, 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.
