Laguna XS 2.1 vs Nemotron 3 Ultra 550B A55B vs Qwen3.6 27B
Laguna XS 2.1 comes out ahead, 68 to 56 and 50 on our weighted score, and it is the cheaper option too.
- Our pick
PoolsideLaguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
NVIDIANemotron 3 Ultra 550B A55B
50/100- ECI146.2
- Price$0.50 / $2.50
- Context1M
Alibaba (Qwen)Qwen3.6 27B
56/100- ECI146.5
- Price$0.60 / $3.60
- Context262K
Laguna XS 2.1 is our pick
Laguna XS 2.1 is the better all-round choice, scoring 68/100 against Qwen3.6 27B (56) and Nemotron 3 Ultra 550B A55B (50). It leads on price. Nemotron 3 Ultra 550B A55B wins on context window. Qwen3.6 27B wins 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 priceLaguna XS 2.1Laguna XS 2.1 $0.075 · Nemotron 3 Ultra 550B A55B $1.00 · Qwen3.6 27B $1.35 per 1M tokens (3:1 blend)
- Longest contextNemotron 3 Ultra 550B A55BNemotron 3 Ultra 550B A55B 1,000,000 · Laguna XS 2.1 262,144 · Qwen3.6 27B 262,144 tokens
- Widest inputsQwen3.6 27BLaguna XS 2.1: Text · Nemotron 3 Ultra 550B A55B: Text · Qwen3.6 27B: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Laguna XS 2.1 | Nemotron 3 Ultra 550B A55B | Qwen3.6 27B |
|---|---|---|---|---|
| Price | 50% | 100 | 50 | 44 |
| Inputs & features | 30% | 35 | 45 | 90 |
| Context window | 20% | 37 | 60 | 37 |
| Overall | 100% | 68/100 | 50/100 | 56/100 |
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 | Laguna XS 2.1Poolside | Nemotron 3 Ultra 550B A55BNVIDIA | Qwen3.6 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 146.2 | 146.5 (best) |
| ECI rank | — | #70 of 148 | #68 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 85.4% | 85.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 35.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 86.7% | 91.1% (best) |
| Price per million tokens | |||
| Input | $0.06 (best) | $0.50 | $0.60 |
| Output | $0.12 (best) | $2.50 | $3.60 |
| Cached input | — | $0.15 | — |
| Blended (3:1) | $0.075 (best) | $1.00 | $1.35 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Nvidia API | Official Alibaba API |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 262,144 tokens |
| Max output | 32,768 tokens | 128,000 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | poolside/laguna-xs-2.1 | nvidia/nemotron-3-ultra-550b-a55b | qwen3.6-27b |
| API providers | 4 | 21 | 27 (best) |
| Released | Jul 2, 2026 | Jun 4, 2026 | Apr 22, 2026 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Laguna XS 2.1$0.84
- Nemotron 3 Ultra 550B A55B$10.00
- Qwen3.6 27B$13.20
Which should you choose?
Which is better: Laguna XS 2.1, Nemotron 3 Ultra 550B A55B or Qwen3.6 27B?
Laguna XS 2.1 is the better all-round choice, scoring 68/100 against Qwen3.6 27B (56) and Nemotron 3 Ultra 550B A55B (50). It leads on price. Nemotron 3 Ultra 550B A55B wins on context window. Qwen3.6 27B wins 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, Laguna XS 2.1, Nemotron 3 Ultra 550B A55B or Qwen3.6 27B?
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 Ultra 550B A55B costs $0.50 input / $2.50 output per million tokens (official Nvidia API price); Qwen3.6 27B costs $0.60 input / $3.60 output per million tokens (official Alibaba 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 $1.00 for Nemotron 3 Ultra 550B A55B (13× as much) and $1.35 for Qwen3.6 27B (18× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Laguna XS 2.1 has not been scored yet, Nemotron 3 Ultra 550B A55B has an ECI of 146.2 and Qwen3.6 27B has an ECI of 146.5.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna XS 2.1, Nemotron 3 Ultra 550B A55B and Qwen3.6 27B 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 Ultra 550B A55B has the largest context window at 1,000,000 tokens, against 262,144 for Laguna XS 2.1 and 262,144 for Qwen3.6 27B. Maximum output per response: Laguna XS 2.1 up to 32,768, Nemotron 3 Ultra 550B A55B up to 128,000, Qwen3.6 27B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Laguna XS 2.1 accepts text; Nemotron 3 Ultra 550B A55B accepts text; Qwen3.6 27B accepts text, images, audio and video. Qwen3.6 27B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Laguna XS 2.1 is the newest, released Jul 2, 2026. Nemotron 3 Ultra 550B A55B came out Jun 4, 2026; Qwen3.6 27B came out Apr 22, 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.
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