Granite 4.2 8B vs Nemotron 3.5 Lightning 30B A3B vs Ling 3.0 Flash VL
Ling 3.0 Flash VL comes out ahead, 76 to 68 and 64 on our weighted score, though Granite 4.2 8B is 8% cheaper per token.
IBMGranite 4.2 8B
64/100- ECI—
- Price$0.06 / $0.15
- Context131K
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
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 Granite 4.2 8B (64). It leads on inputs & features. Granite 4.2 8B wins on price. 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 priceGranite 4.2 8BGranite 4.2 8B $0.083 · Ling 3.0 Flash VL $0.09 · Nemotron 3.5 Lightning 30B A3B $0.091 per 1M tokens (3:1 blend)
- Longest contextNemotron 3.5 Lightning 30B A3B and Ling 3.0 Flash VLNemotron 3.5 Lightning 30B A3B 262,144 · Ling 3.0 Flash VL 262,144 · Granite 4.2 8B 131,072 tokens
- Widest inputsLing 3.0 Flash VLGranite 4.2 8B: Text · Nemotron 3.5 Lightning 30B A3B: Text · Ling 3.0 Flash VL: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Granite 4.2 8B | Nemotron 3.5 Lightning 30B A3B | Ling 3.0 Flash VL |
|---|---|---|---|---|
| Price | 50% | 97 | 95 | 95 |
| Inputs & features | 30% | 35 | 45 | 70 |
| Context window | 20% | 25 | 37 | 37 |
| Overall | 100% | 64/100 | 68/100 | 76/100 |
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 | Granite 4.2 8BIBM | Nemotron 3.5 Lightning 30B A3BNVIDIA | Ling 3.0 Flash VLinclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.06 | $0.055 (best) | $0.06 |
| Output | $0.15 (best) | $0.20 | $0.18 |
| Cached input | — | — | — |
| Blended (3:1) | $0.083 (best) | $0.091 | $0.09 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 10 providers | Median of 7 providers |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 117,964 tokens | 262,144 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | OpenMIT |
| API model ID | — | nvidia/nemotron-3.5-lightning-30b-a3b | — |
| API providers | 7 | 15 (best) | 7 |
| Released | Aug 25, 2026 | Aug 11, 2026 | Sep 10, 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.
- Granite 4.2 8B$0.90
- Nemotron 3.5 Lightning 30B A3B$0.95
- Ling 3.0 Flash VL$0.96
Which should you choose?
Which is better: Granite 4.2 8B, Nemotron 3.5 Lightning 30B A3B or Ling 3.0 Flash VL?
Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Nemotron 3.5 Lightning 30B A3B (68) and Granite 4.2 8B (64). It leads on inputs & features. Granite 4.2 8B wins on price. 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, Granite 4.2 8B, Nemotron 3.5 Lightning 30B A3B or Ling 3.0 Flash VL?
Granite 4.2 8B is cheaper at $0.06 input / $0.15 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 $0.083 per million tokens for Granite 4.2 8B versus $0.09 for Ling 3.0 Flash VL (1.1× as much) and $0.091 for Nemotron 3.5 Lightning 30B A3B (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Granite 4.2 8B has not been scored yet, Nemotron 3.5 Lightning 30B A3B has not been scored yet and Ling 3.0 Flash VL has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite 4.2 8B, Nemotron 3.5 Lightning 30B A3B and Ling 3.0 Flash VL 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 and Ling 3.0 Flash VL have the largest context windows (262,144 and 262,144 tokens), against 131,072 for Granite 4.2 8B. Maximum output per response: Granite 4.2 8B up to 117,964, Nemotron 3.5 Lightning 30B A3B up to 262,144, Ling 3.0 Flash VL up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Granite 4.2 8B accepts text; Nemotron 3.5 Lightning 30B A3B accepts text; Ling 3.0 Flash VL accepts text, images and video. 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. Granite 4.2 8B came out Aug 25, 2026; Nemotron 3.5 Lightning 30B A3B came out Aug 11, 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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