Laguna M.1 vs Mercury 2 vs Nemotron VoiceChat
Too close to call on our weighted score (Laguna M.1 68, Nemotron VoiceChat 65, Mercury 2 53). The right pick depends on what you value most.
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
InceptionMercury 2
53/100- ECI—
- Price$0.25 / $0.75
- Context128K
NVIDIANemotron VoiceChat
65/100- ECI—
- PriceFree / Free
- Context128K
Too close to call
It is close. Our weighted score puts them within 3 points (Laguna M.1 68/100, Nemotron VoiceChat 65/100, Mercury 2 53/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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 Nemotron VoiceChatLaguna M.1 Free · Nemotron VoiceChat Free · Mercury 2 $0.375 per 1M tokens (3:1 blend)
- Longest contextLaguna M.1Laguna M.1 262,144 · Mercury 2 128,000 · Nemotron VoiceChat 128,000 tokens
- Widest inputsNemotron VoiceChatLaguna M.1: Text · Mercury 2: Text · Nemotron VoiceChat: Text, Audio
- Self-hostingLaguna M.1 and Nemotron VoiceChatPublishes downloadable weights
| Measure | Weight | Laguna M.1 | Mercury 2 | Nemotron VoiceChat |
|---|---|---|---|---|
| Price | 50% | 100 | 70 | 100 |
| Inputs & features | 30% | 35 | 45 | 35 |
| Context window | 20% | 37 | 24 | 24 |
| Overall | 100% | 68/100 | 53/100 | 65/100 |
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 M.1Poolside | Mercury 2Inception | Nemotron VoiceChatNVIDIA |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free (best) | $0.25 | Free (best) |
| Output | Free (best) | $0.75 | Free (best) |
| Cached input | — | $0.025 | — |
| Blended (3:1) | Free (best) | $0.375 | Free (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Poolside API | Official Inception API | Official Nvidia API |
| Limits | |||
| Context window | 262,144 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 32,768 tokens | 50,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | poolside/laguna-m.1 | mercury-2 | nvidia/nemotron-voicechat |
| API providers | 2 (best) | 1 | 1 |
| Released | Apr 28, 2026 | Feb 24, 2026 | Mar 16, 2026 |
| Knowledge cutoff | — | Jan 1, 2025 | — |
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
- Mercury 2$4.00
- Nemotron VoiceChatFree
Which should you choose?
Which is better: Laguna M.1, Mercury 2 or Nemotron VoiceChat?
It is close. Our weighted score puts them within 3 points (Laguna M.1 68/100, Nemotron VoiceChat 65/100, Mercury 2 53/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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, Mercury 2 or Nemotron VoiceChat?
Laguna M.1 is cheaper at Free input / Free output per million tokens (official Poolside API price). Nemotron VoiceChat costs Free input / Free output per million tokens (official Nvidia API price); Mercury 2 costs $0.25 input / $0.75 output per million tokens (official Inception API price). 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, Mercury 2 has not been scored yet and Nemotron VoiceChat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna M.1, Mercury 2 and Nemotron VoiceChat 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?
Laguna M.1 has the largest context window at 262,144 tokens, against 128,000 for Mercury 2 and 128,000 for Nemotron VoiceChat. Maximum output per response: Laguna M.1 up to 32,768, Mercury 2 up to 50,000, Nemotron VoiceChat up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Laguna M.1 accepts text; Mercury 2 accepts text; Nemotron VoiceChat accepts text and audio. Nemotron VoiceChat handles the widest range of inputs.
Are any of these open source?
Laguna M.1 and Nemotron VoiceChat publishes its weights and can be self-hosted; Mercury 2 is proprietary.
Which is newer?
Laguna M.1 is the newest, released Apr 28, 2026. Nemotron VoiceChat came out Mar 16, 2026; Mercury 2 came out Feb 24, 2026. Knowledge cutoff: Mercury 2 Jan 1, 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.
