MiniMax-M2.7-highspeed vs Nemotron VoiceChat vs Qwen3.5 122B-A10B
Nemotron VoiceChat comes out ahead, 65 to 58 and 41 on our weighted score, and it is the cheaper option too.
MiniMaxMiniMax-M2.7-highspeed
41/100- ECI—
- Price$0.60 / $2.40
- Context205K
- Our pick
NVIDIANemotron VoiceChat
65/100- ECI—
- PriceFree / Free
- Context128K
Alibaba (Qwen)Qwen3.5 122B-A10B
58/100- ECI—
- Price$0.40 / $3.20
- Context262K
Nemotron VoiceChat is our pick
Nemotron VoiceChat is the better all-round choice, scoring 65/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.7-highspeed (41). It leads on price. Qwen3.5 122B-A10B wins 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 priceNemotron VoiceChatNemotron VoiceChat Free · MiniMax-M2.7-highspeed $1.05 · Qwen3.5 122B-A10B $1.10 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10BQwen3.5 122B-A10B 262,144 · MiniMax-M2.7-highspeed 204,800 · Nemotron VoiceChat 128,000 tokens
- Widest inputsQwen3.5 122B-A10BMiniMax-M2.7-highspeed: Text · Nemotron VoiceChat: Text, Audio · Qwen3.5 122B-A10B: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | MiniMax-M2.7-highspeed | Nemotron VoiceChat | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 49 | 100 | 48 |
| Inputs & features | 30% | 35 | 35 | 90 |
| Context window | 20% | 32 | 24 | 37 |
| Overall | 100% | 41/100 | 65/100 | 58/100 |
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 | MiniMax-M2.7-highspeedMiniMax | Nemotron VoiceChatNVIDIA | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | Free (best) | $0.40 |
| Output | $2.40 | Free (best) | $3.20 |
| Cached input | $0.06 | — | — |
| Blended (3:1) | $1.05 | Free (best) | $1.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Nvidia API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 8,192 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | Yes |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | MiniMax-M2.7-highspeed | nvidia/nemotron-voicechat | qwen3.5-122b-a10b |
| API providers | 14 | 1 | 19 (best) |
| Released | Mar 18, 2026 | Mar 16, 2026 | Feb 23, 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.
- MiniMax-M2.7-highspeed$10.80
- Nemotron VoiceChatFree
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: MiniMax-M2.7-highspeed, Nemotron VoiceChat or Qwen3.5 122B-A10B?
Nemotron VoiceChat is the better all-round choice, scoring 65/100 against Qwen3.5 122B-A10B (58) and MiniMax-M2.7-highspeed (41). It leads on price. Qwen3.5 122B-A10B wins 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, MiniMax-M2.7-highspeed, Nemotron VoiceChat or Qwen3.5 122B-A10B?
Nemotron VoiceChat is cheaper at Free input / Free output per million tokens (official Nvidia API price). MiniMax-M2.7-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price); Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price). Nemotron VoiceChat is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2.7-highspeed has not been scored yet, Nemotron VoiceChat has not been scored yet and Qwen3.5 122B-A10B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.7-highspeed, Nemotron VoiceChat and Qwen3.5 122B-A10B 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?
Qwen3.5 122B-A10B has the largest context window at 262,144 tokens, against 204,800 for MiniMax-M2.7-highspeed and 128,000 for Nemotron VoiceChat. Maximum output per response: MiniMax-M2.7-highspeed up to 131,072, Nemotron VoiceChat up to 8,192, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.7-highspeed accepts text; Nemotron VoiceChat accepts text and audio; Qwen3.5 122B-A10B accepts text, images, audio and video. Qwen3.5 122B-A10B 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?
MiniMax-M2.7-highspeed is the newest, released Mar 18, 2026. Nemotron VoiceChat came out Mar 16, 2026; Qwen3.5 122B-A10B came out Feb 23, 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.
