Nemotron 3.5 Lightning 30B A3B vs Ling 3.0 Flash VL vs Ling 3.0 Flash
Ling 3.0 Flash VL comes out ahead, 76 to 68 and 65 on our weighted score.
NVIDIANemotron 3.5 Lightning 30B A3B
68/100- ECI—
- Price$0.055 / $0.20
- Context262K
- Our pick
inclusionAILing 3.0 Flash VL
76/100- ECI—
- Price$0.06 / $0.18
- Context262K
- inclusionAI
Ling 3.0 Flash
65/100- ECI—
- Price$0.06 / $0.18
- 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 VL and Ling 3.0 FlashLing 3.0 Flash VL $0.09 · Ling 3.0 Flash $0.09 · Nemotron 3.5 Lightning 30B A3B $0.091 per 1M tokens (3:1 blend)
- Longest contextAbout the sameNemotron 3.5 Lightning 30B A3B 262,144 · Ling 3.0 Flash VL 262,144 · Ling 3.0 Flash 262,144 tokens
- Widest inputsLing 3.0 Flash VLNemotron 3.5 Lightning 30B A3B: Text · Ling 3.0 Flash VL: Text, Images, Video · Ling 3.0 Flash: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Nemotron 3.5 Lightning 30B A3B | Ling 3.0 Flash VL | Ling 3.0 Flash |
|---|---|---|---|---|
| Price | 50% | 95 | 95 | 95 |
| Inputs & features | 30% | 45 | 70 | 35 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 68/100 | 76/100 | 65/100 |
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 | Nemotron 3.5 Lightning 30B A3BNVIDIA | Ling 3.0 Flash VLinclusionAI | Ling 3.0 FlashinclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.055 (best) | $0.06 | $0.06 |
| Output | $0.20 | $0.18 (best) | $0.18 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.091 | $0.09 (best) | $0.09 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 10 providers | Median of 7 providers | Median of 7 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 262,144 tokens (best) | 32,768 tokens | 32,768 tokens |
| 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 | Yes | No | No |
| Availability | |||
| Weights | Open | OpenMIT | OpenMIT |
| API model ID | nvidia/nemotron-3.5-lightning-30b-a3b | — | — |
| API providers | 15 (best) | 7 | 9 |
| Released | Aug 11, 2026 | Sep 10, 2026 | Jul 23, 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.
- Nemotron 3.5 Lightning 30B A3B$0.95
- Ling 3.0 Flash VL$0.96
- Ling 3.0 Flash$0.96
Which should you choose?
Which is better: Nemotron 3.5 Lightning 30B A3B, Ling 3.0 Flash VL or Ling 3.0 Flash?
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, Nemotron 3.5 Lightning 30B A3B, Ling 3.0 Flash VL or Ling 3.0 Flash?
Ling 3.0 Flash VL is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). Ling 3.0 Flash 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 VL versus $0.09 for Ling 3.0 Flash (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. Nemotron 3.5 Lightning 30B A3B has not been scored yet, Ling 3.0 Flash VL has not been scored yet and Ling 3.0 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3.5 Lightning 30B A3B, Ling 3.0 Flash VL and Ling 3.0 Flash 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?
Nemotron 3.5 Lightning 30B A3B, Ling 3.0 Flash VL and Ling 3.0 Flash share the same 262,144-token context window. Maximum output per response: Nemotron 3.5 Lightning 30B A3B up to 262,144, Ling 3.0 Flash VL up to 32,768, Ling 3.0 Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3.5 Lightning 30B A3B accepts text; Ling 3.0 Flash VL accepts text, images and video; Ling 3.0 Flash 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.
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