Top picks for Chat Companion (2026)
General-purpose conversation. Ranked from 405 live models on the OpenRouter catalog, weighted for low cost, low latency, reasoning quality.
| # | Model | Score | In / 1M | Out / 1M | Context | |
|---|---|---|---|---|---|---|
| 1 | OpenAI: GPT-5.6 Lunaopenai/gpt-5.6-luna | 132 | $0.10 | $0.60 | 1,050,000 | Details → |
| 2 | OpenAI: GPT-5.6 Luna (batch)openai/gpt-5.6-luna:batch | 132 | $0.10 | $0.60 | 1,050,000 | Details → |
| 3 | Z.ai: GLM 5.2 (batch)z-ai/glm-5.2:batch | 132 | $0.70 | $2.20 | 512,000 | Details → |
| 4 | OpenAI: GPT-5 (batch)openai/gpt-5:batch | 131 | $0.62 | $5.00 | 400,000 | Details → |
| 5 | MoonshotAI: Kimi K2.6moonshotai/kimi-k2.6 | 131 | $0.95 | $4.00 | 262,144 | Details → |
| 6 | Z.ai: GLM 5.2z-ai/glm-5.2 | 131 | $0.50 | $3.15 | 1,048,576 | Details → |
| 7 | Google: Gemini 3.6 Flash (batch)google/gemini-3.6-flash:batch | 131 | $0.75 | $3.75 | 1,048,576 | Details → |
| 8 | MiniMax: MiniMax M3 (batch)minimax/minimax-m3:batch | 131 | $0.15 | $0.60 | 524,288 | Details → |
| 9 | MiniMax: MiniMax M3minimax/minimax-m3 | 131 | $0.30 | $1.20 | 1,048,576 | Details → |
| 10 | Google: Gemini 3.5 Flash (batch)google/gemini-3.5-flash:batch | 131 | $0.75 | $4.50 | 1,048,576 | Details → |
| 11 | Upstage: Solar Pro 4upstage/solar-pro4 | 130 | $0.03 | $0.12 | 524,288 | Details → |
| 12 | MoonshotAI: Kimi K2.7 Code (batch)moonshotai/kimi-k2.7-code:batch | 130 | $0.47 | $2.00 | 262,144 | Details → |
| 13 | Thinking Machines: Inkling Smallthinkingmachines/inkling-small | 130 | $0.45 | $1.20 | 524,288 | Details → |
| 14 | Thinking Machines: Inkling (batch)thinkingmachines/inkling:batch | 130 | $0.50 | $2.02 | 524,288 | Details → |
| 15 | OpenAI: GPT-5.4 Nano (batch)openai/gpt-5.4-nano:batch | 130 | $0.10 | $0.62 | 400,000 | Details → |
How we ranked these
For Chat Companion, we weight models on low cost, low latency, reasoning quality. Scores combine each model's public specs with independent benchmark results (Aider Polyglot coding scores, Artificial Analysis intelligence/coding/agentic indices) and live pricing. See full methodology →
About Chat Companion
Chat Companion is a general-purpose conversational AI task for sustained dialogue across topics without specialized domain requirements. Use this when you need a model to maintain context, respond naturally, and handle topic switches without retraining or task-specific setup. Good models maintain coherence over 10+ exchanges, avoid repetitive phrasing, and generate responses in under 2 seconds per turn. Poor performers lose context mid-conversation, repeat themselves, or respond with generic filler. The main cost consideration: longer conversations consume more tokens, so batch-processing multiple chats costs more than single-turn Q&A, but streaming responses to users reduces perceived latency significantly.
When to use: Use this when you want an AI that can chat naturally with you about anything, remember what you said earlier in the conversation, and keep talking without you having to re-explain context.
Common questions
Which AI models are best for chat companions?
GPT-4 and Claude 3.5 Sonnet lead for extended conversations due to stronger context retention and more natural tone. For cost-sensitive applications, GPT-4o Mini and Claude 3.5 Haiku deliver solid performance at 80-90% of flagship quality while cutting costs by 70-80%.
How much does it cost to run a chat companion for hours per day?
Costs depend on your model choice and conversation length. A typical 10-exchange conversation uses 2,000-4,000 tokens and costs $0.01-0.10 on budget models or $0.05-0.50 on flagship models. For continuous all-day usage, expect $2-15 daily per active user with a mid-tier model.