Nemotron VoiceChat vs GLM-4.5-Flash vs Laguna M.1
Too close to call on our weighted score (Laguna M.1 68, GLM-4.5-Flash 65, Nemotron VoiceChat 65). The right pick depends on what you value most.
NVIDIANemotron VoiceChat
65/100- ECI—
- PriceFree / Free
- Context128K
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Laguna M.1 68/100, GLM-4.5-Flash 65/100, Nemotron VoiceChat 65/100), so choose by what matters most for your work: Nemotron VoiceChat 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 priceSame priceNemotron VoiceChat Free · GLM-4.5-Flash Free · Laguna M.1 Free per 1M tokens (3:1 blend)
- Longest contextLaguna M.1Laguna M.1 262,144 · GLM-4.5-Flash 131,072 · Nemotron VoiceChat 128,000 tokens
- Widest inputsNemotron VoiceChatNemotron VoiceChat: Text, Audio · GLM-4.5-Flash: Text · Laguna M.1: Text
- Self-hostingNemotron VoiceChat and Laguna M.1Publishes downloadable weights
| Measure | Weight | Nemotron VoiceChat | GLM-4.5-Flash | Laguna M.1 |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 24 | 24 | 37 |
| Overall | 100% | 65/100 | 65/100 | 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 VoiceChatNVIDIA | GLM-4.5-FlashZ.ai (Zhipu) | Laguna M.1Poolside |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free | Free | Free |
| Output | Free | Free | Free |
| Cached input | — | — | — |
| Blended (3:1) | Free | Free | Free |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Nvidia API | Official Z.AI API | Official Poolside API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 98,304 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | nvidia/nemotron-voicechat | glm-4.5-flash | poolside/laguna-m.1 |
| API providers | 1 | 4 (best) | 2 |
| Released | Mar 16, 2026 | Jul 28, 2025 | Apr 28, 2026 |
| Knowledge cutoff | — | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Nemotron VoiceChatFree
- GLM-4.5-FlashFree
- Laguna M.1Free
Which should you choose?
Which is better: Nemotron VoiceChat, GLM-4.5-Flash or Laguna M.1?
It is close. Our weighted score puts them within 2 points (Laguna M.1 68/100, GLM-4.5-Flash 65/100, Nemotron VoiceChat 65/100), so choose by what matters most for your work: Nemotron VoiceChat 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, Nemotron VoiceChat, GLM-4.5-Flash or Laguna M.1?
Nemotron VoiceChat, GLM-4.5-Flash 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 all three models yet. Nemotron VoiceChat has not been scored yet, GLM-4.5-Flash 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 Nemotron VoiceChat, GLM-4.5-Flash and Laguna M.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?
Laguna M.1 has the largest context window at 262,144 tokens, against 131,072 for GLM-4.5-Flash and 128,000 for Nemotron VoiceChat. Maximum output per response: Nemotron VoiceChat up to 8,192, GLM-4.5-Flash up to 98,304, Laguna M.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Nemotron VoiceChat accepts text and audio; GLM-4.5-Flash accepts text; Laguna M.1 accepts text. Nemotron VoiceChat handles the widest range of inputs.
Are any of these open source?
Nemotron VoiceChat and Laguna M.1 publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
Laguna M.1 is the newest, released Apr 28, 2026. Nemotron VoiceChat came out Mar 16, 2026; GLM-4.5-Flash came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Flash Apr 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.
