Nemotron 3.5 Lightning 30B A3B vs GPT-5.6 Cyber vs Laguna XS 2.1
Nemotron 3.5 Lightning 30B A3B comes out ahead, 71 to 68 and 30 on our weighted score, though Laguna XS 2.1 is 14% cheaper per token.
- Our pick
NVIDIANemotron 3.5 Lightning 30B A3B
71/100- ECI—
- Price$0.05 / $0.20
- Context262K
OpenAIGPT-5.6 Cyber
30/100- ECI—
- Price$12.50 / $75.00
- Context400K
PoolsideLaguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
Nemotron 3.5 Lightning 30B A3B is our pick
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Laguna XS 2.1 (68) and GPT-5.6 Cyber (30). GPT-5.6 Cyber wins 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 priceLaguna XS 2.1Laguna XS 2.1 $0.075 · Nemotron 3.5 Lightning 30B A3B $0.087 · GPT-5.6 Cyber $28.13 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 CyberGPT-5.6 Cyber 400,000 · Nemotron 3.5 Lightning 30B A3B 262,144 · Laguna XS 2.1 262,144 tokens
- Widest inputsGPT-5.6 CyberNemotron 3.5 Lightning 30B A3B: Text · GPT-5.6 Cyber: Text, Images · Laguna XS 2.1: Text
- Self-hostingNemotron 3.5 Lightning 30B A3B and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Nemotron 3.5 Lightning 30B A3B | GPT-5.6 Cyber | Laguna XS 2.1 |
|---|---|---|---|---|
| Price | 50% | 100 | 0 | 100 |
| Inputs & features | 30% | 45 | 70 | 35 |
| Context window | 20% | 37 | 44 | 37 |
| Overall | 100% | 71/100 | 30/100 | 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 | Nemotron 3.5 Lightning 30B A3BNVIDIA | GPT-5.6 CyberOpenAI | Laguna XS 2.1Poolside |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $12.50 | $0.06 |
| Output | $0.20 | $75.00 | $0.12 (best) |
| Cached input | — | $1.25 | — |
| Blended (3:1) | $0.087 | $28.13 | $0.075 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 9 providers | Official OpenAI API | Median of 1 providers |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens (best) | 262,144 tokens |
| Max output | 262,144 tokens (best) | 128,000 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 | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | nvidia/nemotron-3.5-lightning-30b-a3b | gpt-daybreak-red-latest | poolside/laguna-xs-2.1 |
| API providers | 12 (best) | 1 | 4 |
| Released | Aug 11, 2026 | Aug 7, 2026 | Jul 2, 2026 |
| Knowledge cutoff | — | Feb 16, 2026 | — |
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$0.90
- GPT-5.6 Cyber$275.00
- Laguna XS 2.1$0.84
Which should you choose?
Which is better: Nemotron 3.5 Lightning 30B A3B, GPT-5.6 Cyber or Laguna XS 2.1?
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Laguna XS 2.1 (68) and GPT-5.6 Cyber (30). GPT-5.6 Cyber wins 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, Nemotron 3.5 Lightning 30B A3B, GPT-5.6 Cyber or Laguna XS 2.1?
Laguna XS 2.1 is cheaper at $0.06 input / $0.12 output per million tokens (median across 1 API provider; free on Poolside). Nemotron 3.5 Lightning 30B A3B costs $0.05 input / $0.20 output per million tokens (median across 9 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 $0.075 per million tokens for Laguna XS 2.1 versus $0.087 for Nemotron 3.5 Lightning 30B A3B (1.2× as much) and $28.13 for GPT-5.6 Cyber (375× 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, GPT-5.6 Cyber has not been scored yet and Laguna XS 2.1 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, GPT-5.6 Cyber and Laguna XS 2.1 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 Nemotron 3.5 Lightning 30B A3B and 262,144 for Laguna XS 2.1. Maximum output per response: Nemotron 3.5 Lightning 30B A3B up to 262,144, GPT-5.6 Cyber up to 128,000, Laguna XS 2.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3.5 Lightning 30B A3B accepts text; GPT-5.6 Cyber accepts text and images; Laguna XS 2.1 accepts text. GPT-5.6 Cyber handles the widest range of inputs.
Are any of these open source?
Nemotron 3.5 Lightning 30B A3B and Laguna XS 2.1 publishes its weights and can be self-hosted; GPT-5.6 Cyber is proprietary.
Which is newer?
Nemotron 3.5 Lightning 30B A3B is the newest, released Aug 11, 2026. GPT-5.6 Cyber came out Aug 7, 2026; Laguna XS 2.1 came out Jul 2, 2026. Knowledge cutoff: GPT-5.6 Cyber Feb 16, 2026.
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 Oct 4, 2026.
