Nova 2 Pro vs Laguna M.1
Nova 2 Pro comes out ahead, 86 to 68 on our weighted score.
- Our pick
AmazonNova 2 Pro
86/100- ECI—
- PriceFree / Free
- Context1M
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
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Make it a three-way comparison.
Nova 2 Pro is our pick
Nova 2 Pro is the better all-round choice, scoring 86/100 against Laguna M.1 (68). It leads 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 priceSame priceNova 2 Pro Free · Laguna M.1 Free per 1M tokens (3:1 blend)
- Longest contextNova 2 ProNova 2 Pro 1,000,000 · Laguna M.1 262,144 tokens
- Widest inputsNova 2 ProNova 2 Pro: Text, Images, PDFs, Video · Laguna M.1: Text
- Self-hostingLaguna M.1Publishes downloadable weights
| Measure | Weight | Nova 2 Pro | Laguna M.1 |
|---|---|---|---|
| Price | 50% | 100 | 100 |
| Inputs & features | 30% | 80 | 35 |
| Context window | 20% | 60 | 37 |
| Overall | 100% | 86/100 | 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 | Nova 2 ProAmazon | Laguna M.1Poolside |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | Free | Free |
| Output | Free | Free |
| Cached input | — | — |
| Blended (3:1) | Free | Free |
| Long-context rate | Same rate | Same rate |
| Price source | Official Nova API | Official Poolside API |
| Limits | ||
| Context window | 1,000,000 tokens (best) | 262,144 tokens |
| Max output | 64,000 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | nova-2-pro-v1 | poolside/laguna-m.1 |
| API providers | 1 | 2 (best) |
| Released | Dec 3, 2025 | Apr 28, 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.
- Nova 2 ProFree
- Laguna M.1Free
Which should you choose?
Which is better: Nova 2 Pro or Laguna M.1?
Nova 2 Pro is the better all-round choice, scoring 86/100 against Laguna M.1 (68). It leads 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, Nova 2 Pro or Laguna M.1?
Nova 2 Pro and Laguna M.1 cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Nova 2 Pro has not been scored yet and Laguna M.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nova 2 Pro and Laguna M.1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Nova 2 Pro has the largest context window at 1,000,000 tokens, against 262,144 for Laguna M.1. Maximum output per response: Nova 2 Pro up to 64,000, Laguna M.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Nova 2 Pro accepts text, images, PDFs and video; Laguna M.1 accepts text. Nova 2 Pro handles the widest range of inputs.
Are any of these open source?
Laguna M.1 publishes its weights and can be self-hosted; Nova 2 Pro is proprietary.
Which is newer?
Laguna M.1 is the newest, released Apr 28, 2026. Nova 2 Pro came out Dec 3, 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 Oct 4, 2026.
