Models Reference
How models work on the Tensor Machine API — a single OpenAI-compatible endpoint, India-resident. The live catalogue and current pricing are on the website.
Available models
Tensor Machine serves a catalogue of frontier models via a single OpenAI-compatible API endpoint. All models run on India-resident infrastructure.
The examples below are illustrative — the live catalogue is larger and changes often, and current pricing lives on the website, not here. For the up-to-date model list, context windows, and per-model INR rates, see tensormachine.ai/models and tensormachine.ai/pricing.
Example models
A few representative models and the kinds of work they suit (not the full list, and not pricing — check the live catalogue for both):
| Model ID | Provider | Context | Type |
|---|---|---|---|
z-ai/glm-5.2 | Z-AI | 1M | Chat, Code |
minimax/minimax-m3 | MiniMax | 1M | Chat, Code, Vision |
deepseek/deepseek-v4-pro | DeepSeek | 1M | Chat, Code |
deepseek/deepseek-v4-flash | DeepSeek | 1M | Chat |
moonshotai/kimi-k2.6 | MoonshotAI | 256K | Chat |
moonshotai/kimi-k2.7-code | MoonshotAI | 256K | Code |
qwen/qwen3-235b-a22b | Alibaba | 128K | Chat, Code |
meta-llama/llama-4-maverick | Meta | 1M | Chat, Vision |
google/gemma-3-27b | 128K | Chat |
View the full, current library — with filtering and live pricing — at tensormachine.ai/models.
API endpoint
All models are accessed via:
POST https://edge.tensormachine.ai/v1/chat/completionsThe request format is identical to the OpenAI Chat Completions API.
Choosing a model
| Scenario | Recommended model |
|---|---|
| High-volume chat at low cost | deepseek/deepseek-v4-flash |
| Complex reasoning & coding | deepseek/deepseek-v4-pro |
| Long document analysis (1M ctx) | z-ai/glm-5.2 or minimax/minimax-m3 |
| Image understanding | minimax/minimax-m3 or meta-llama/llama-4-maverick |
| Code generation | moonshotai/kimi-k2.7-code |
| Multilingual (Hindi, etc.) | moonshotai/kimi-k2.6 |
| Budget-friendly open model | google/gemma-3-27b |
Model parameters
All standard OpenAI parameters are supported:
| Parameter | Description |
|---|---|
model | Model ID (required) |
messages | Conversation history (required) |
max_tokens | Maximum tokens to generate |
temperature | Sampling temperature (0–2) |
top_p | Nucleus sampling |
stream | Enable streaming (SSE) |
stop | Stop sequences |
n | Number of completions |
Requesting new models
If you need a model not yet on the platform, request it from the console (Models → Request a model). We pool demand and stand up dedicated deployments on a first-come, first-served basis — see how model requests work.