Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
- Kimi K3.1 Pro
- DeepSeek V4.1 Flash 1017
- Nemotron 3.5 Super VL
- Gemini 4 Argon
- Muse Wonder
- Gemini 3.1 Flash Lite Image (Google Vertex AI)
- Gemini 3.1 Flash Lite Image (Google AI Studio)Enterprise & partner access
- Gemini 3.1 Flash Image (Google Vertex AI)Enterprise & partner access
| Attribute | Kimi K2 0905kimi-k2-0905 | Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free | Muse Spark Openmuse-spark-open |
|---|---|---|---|
| Pricing | |||
| Input | $0.60 / 1M | $0 / 1M | $1.25 / 1M |
| Output | $2.50 / 1M | $0 / 1M | $4.25 / 1M |
| Cache Write (5m) | $0.60 / 1M | — | $1.25 / 1M |
| Cache Write (1h) | $0.60 / 1M | — | $1.25 / 1M |
| Cache Read | $0.60 / 1M | $0 / 1M | $1.25 / 1M |
| Web Search | $0 / 1M | — | $0 / 1M |
| Cache Write | — | $0 / 1M | — |
| Context | |||
| Max context | 262K | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Moonshot AI | NVIDIA | Meta |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Free | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Kimi K2-Instruct-0905 is the newest and strongest Kimi K2 model — a trillion-parameter MoE system with 32B active parameters. It delivers major gains in agentic coding, better frontend development results, and an expanded 256K context window for longer tasks. | NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications. | Muse Spark Open is an open-weight, coding-optimized model designed for agentic software engineering workflows. It delivers strong first-attempt accuracy, reliable tool calling, and deep codebase understanding, enabling effective development across real-world repositories. Optimized for autonomous coding agents, complex code navigation, and tool-driven development, Muse Spark Open is well suited for software engineering automation, debugging, code generation, and multi-step coding workflows where accuracy and reliable execution are essential. |