GPT-5.6 Cyber 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 30 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.6 Cyber
30/100- ECI—
- Price$12.50 / $75.00
- Context400K
- Our pick
inclusionAILing 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 GPT-5.6 Cyber (30). GPT-5.6 Cyber wins on 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 Flash VLLing 3.0 Flash VL $0.09 · Nemotron 3.5 Lightning 30B A3B $0.091 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 CyberGPT-5.6 Cyber 400,000 · Ling 3.0 Flash VL 262,144 · Nemotron 3.5 Lightning 30B A3B 262,144 tokens
- Widest inputsLing 3.0 Flash VLGPT-5.6 Cyber: Text, Images · Ling 3.0 Flash VL: Text, Images, Video · Nemotron 3.5 Lightning 30B A3B: Text
- Self-hostingLing 3.0 Flash VL and Nemotron 3.5 Lightning 30B A3BPublishes downloadable weights (MIT)
| Measure | Weight | GPT-5.6 Cyber | Ling 3.0 Flash VL | Nemotron 3.5 Lightning 30B A3B |
|---|---|---|---|---|
| Price | 50% | 0 | 95 | 95 |
| Inputs & features | 30% | 70 | 70 | 45 |
| Context window | 20% | 44 | 37 | 37 |
| Overall | 100% | 30/100 | 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 | GPT-5.6 CyberOpenAI | Ling 3.0 Flash VLinclusionAI | Nemotron 3.5 Lightning 30B A3BNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $12.50 | $0.06 | $0.055 (best) |
| Output | $75.00 | $0.18 (best) | $0.20 |
| Cached input | $1.25 | — | — |
| Blended (3:1) | $28.13 | $0.09 (best) | $0.091 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 7 providers | Median of 10 providers |
| Limits | |||
| Context window | 400,000 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 128,000 tokens | 32,768 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | OpenMIT | Open |
| API model ID | gpt-daybreak-red-latest | — | nvidia/nemotron-3.5-lightning-30b-a3b |
| API providers | 1 | 7 | 15 (best) |
| Released | Aug 7, 2026 | Sep 10, 2026 | Aug 11, 2026 |
| Knowledge cutoff | Feb 16, 2026 | — | 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.
- GPT-5.6 Cyber$275.00
- Ling 3.0 Flash VL$0.96
- Nemotron 3.5 Lightning 30B A3B$0.95
Which should you choose?
Which is better: GPT-5.6 Cyber, 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 GPT-5.6 Cyber (30). GPT-5.6 Cyber wins on 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, GPT-5.6 Cyber, Ling 3.0 Flash VL or Nemotron 3.5 Lightning 30B A3B?
Ling 3.0 Flash VL 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); GPT-5.6 Cyber costs $12.50 input / $75.00 output per million tokens (official OpenAI 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 $0.091 for Nemotron 3.5 Lightning 30B A3B (1× as much) and $28.13 for GPT-5.6 Cyber (313× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.6 Cyber 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 GPT-5.6 Cyber, 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?
GPT-5.6 Cyber has the largest context window at 400,000 tokens, against 262,144 for Ling 3.0 Flash VL and 262,144 for Nemotron 3.5 Lightning 30B A3B. Maximum output per response: GPT-5.6 Cyber up to 128,000, 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?
GPT-5.6 Cyber accepts text and images; 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?
Ling 3.0 Flash VL and Nemotron 3.5 Lightning 30B A3B publishes its weights (MIT) and can be self-hosted; GPT-5.6 Cyber is proprietary.
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; GPT-5.6 Cyber came out Aug 7, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026, 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.
