Laguna M.1 vs North Small Translate vs Qwen3.8 Flash Next
Too close to call on our weighted score (Qwen3.8 Flash Next 70, Laguna M.1 68, North Small Translate 50). The right pick depends on what you value most.
Poolside
Laguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
Cohere
North Small Translate
50/100- ECI—
- PriceFree / Free
- Context16K
Alibaba (Qwen)
Qwen3.8 Flash Next
70/100- ECI—
- Price$0.20 / $0.50
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Qwen3.8 Flash Next 70/100, Laguna M.1 68/100, North Small Translate 50/100), so choose by what matters most for your work: Laguna M.1 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 priceLaguna M.1 and North Small TranslateLaguna M.1 Free · North Small Translate Free · Qwen3.8 Flash Next $0.275 per 1M tokens (3:1 blend)
- Longest contextLaguna M.1 and Qwen3.8 Flash NextLaguna M.1 262,144 · Qwen3.8 Flash Next 262,144 · North Small Translate 16,000 tokens
- Widest inputsQwen3.8 Flash NextLaguna M.1: Text · North Small Translate: Text · Qwen3.8 Flash Next: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Laguna M.1 | North Small Translate | Qwen3.8 Flash Next |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 76 |
| Inputs & features | 30% | 35 | 0 | 80 |
| Context window | 20% | 37 | 0 | 37 |
| Overall | 100% | 68/100 | 50/100 | 70/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free (best) | Free (best) | $0.20 |
| Output | Free (best) | Free (best) | $0.50 |
| Cached input | — | — | — |
| Blended (3:1) | Free (best) | Free (best) | $0.275 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Poolside API | Official Cohere API | Median of 5 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 16,000 tokens | 262,144 tokens (best) |
| Max output | 32,768 tokens | 16,000 tokens | 131,072 tokens (best) |
| 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 | No | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenCC-BY-NC-4.0 | Openqwen-community-1.0 |
| API model ID | poolside/laguna-m.1 | north-small-translate-09-2026 | — |
| API providers | 2 | 1 | 5 (best) |
| Released | Apr 28, 2026 | Sep 9, 2026 | Aug 27, 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 M.1Free
North Small TranslateFree
Qwen3.8 Flash Next$3.00
Which should you choose?
Which is better: Laguna M.1, North Small Translate or Qwen3.8 Flash Next?
It is close. Our weighted score puts them within 2 points (Qwen3.8 Flash Next 70/100, Laguna M.1 68/100, North Small Translate 50/100), so choose by what matters most for your work: Laguna M.1 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, Laguna M.1, North Small Translate or Qwen3.8 Flash Next?
Laguna M.1 is cheaper at Free input / Free output per million tokens (official Poolside API price). North Small Translate costs Free input / Free output per million tokens (official Cohere API price); Qwen3.8 Flash Next costs $0.20 input / $0.50 output per million tokens (median across 5 API providers). Laguna M.1 is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Laguna M.1 has not been scored yet, North Small Translate has not been scored yet and Qwen3.8 Flash Next has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna M.1, North Small Translate and Qwen3.8 Flash Next yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that North Small Translate does not support tool calling, which most coding agents need.
Which has the bigger context window?
Laguna M.1 and Qwen3.8 Flash Next have the largest context windows (262,144 and 262,144 tokens), against 16,000 for North Small Translate. Maximum output per response: Laguna M.1 up to 32,768, North Small Translate up to 16,000, Qwen3.8 Flash Next up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Laguna M.1 accepts text; North Small Translate accepts text; Qwen3.8 Flash Next accepts text, images and video. Qwen3.8 Flash Next handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (CC-BY-NC-4.0 and qwen-community-1.0), so you can self-host them.
Which is newer?
North Small Translate is the newest, released Sep 9, 2026. Qwen3.8 Flash Next came out Aug 27, 2026; Laguna M.1 came out Apr 28, 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.