Mistral AI Titan is better suited for complex tasks requiring multilingual support, code generation, and reasoning, while Inflection AI Pi++ is optimized for empathetic conversations and customer support. Inflection-2's industry-leading context window length of 200k tokens makes it ideal for tasks requiring long-term memory. The choice depends on the specific application and priorities.
| Attribute | Mistral AI Titan | Inflection AI Pi++ |
|---|---|---|
| Model Size (Number of Parameters) | Mistral Large 2 has 123 billion parameters. | Pi: 13 billion parameters, Inflection-2: 175 billion parameters (speculated to be 400 billion) |
| Context Window Length | Mistral Large 2 features a 128k token context window. Mistral 7B uses sliding window attention (SWA) trained with an 8K context length. PoSE training can extend Mistral 7B's context window to 32k. | Pi: Approximately 1000 tokens (750 words), Productivity model: 8k tokens, Inflection-2: 200K tokens |
| Training Data Composition and Size | Mistral Large 2 was trained on a large proportion of multilingual data. | Inflection-2: Trained on 5,000 NVIDIA H100 GPUs, utilizing fp8 mixed precision, to achieve around 10 FLOPs. Qwen3-Coder: 7.5 trillion tokens of pre-training data, with 70% dedicated to code. |
| Finetuning Capabilities and Customization Options | Mistral provides options for fine-tuning, including paid plans. They offer an SDK (Mistral-Finetune) optimized for multi-GPU setups but scalable to a single GPU. Fine-tuning services are available via API and custom training services for select customers. The fine-tuning API and SDK allow users to fine-tune and deploy custom Mistral models. You can fine-tune on your own infrastructure or through Mistral's managed fine-tuning services. LoRA (Low-Rank Adaptation) is used for efficient fine-tuning. | Inflection for Enterprise: Proprietary fine-tuning system using reinforcement learning from employee feedback. |
| Multilingual Support (Number of Languages and Performance) | Mistral Large has native multilingual capacities in English, French, Spanish, German, and Italian. Mistral Large 2 supports dozens of languages, including French, German, Italian, Spanish, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, and is trained on extensive multilingual data. It maintains consistent performance across languages. | Qwen3-Coder: Supports a vast array of programming languages (C++, Python, Java, ABAP, Rust, Swift, etc.) |
| Inference Speed and Latency | Mistral Small is optimized for latency and cost. | Inflection-2: Reportedly faster than its predecessor. |
| Hardware Requirements and Optimization | Models need to load completely into RAM or VRAM for each new token generation. High-end GPUs (NVIDIA RTX 3090 or 4090) or dual GPU setups are recommended for the largest models. A system with a minimum of 16 GB RAM (64 GB recommended) is optimal. Consider GGML/GGUF models if budget is limited. Having CPU instruction sets like AVX, AVX2, AVX-512 can improve performance. For Mistral 7B, a minimum of 16GB VRAM is needed for full precision. | Utilizes AI-optimized Azure virtual machines with InfiniBand networking, Intel's Gaudi 3 AI accelerators, and Intel Tiber AI Cloud. Inflection-2 was trained on 5,000 NVIDIA H100 GPUs. |
| API Availability and Ease of Integration | Mistral Large is available through La Plateforme and Azure. | Inflection AI provides APIs to access their models for building conversational AI applications. |
| Pricing Model and Cost-Effectiveness | Mistral AI uses a token-based pricing model. They offer a range of models with competitive pricing. Mistral AI price starts at $0 for hobbyists, scales to custom six-figure enterprise contracts. | Pi and Productivity models: $2.50 per 1M input tokens and $10 per 1M output tokens. |
| Safety Measures and Bias Mitigation | Mistral uses a system prompt to reduce harmful outputs. They have a content moderation API to classify harmful content. Mistral models can act as content moderators. They are committed to generative AI principles to prevent child sexual abuse. | Aims to avoid racist, sexist, or violent behavior. Has a safety policy to avoid hallucinations and remain doubtful of itself. |
| Hallucination Rate and Factuality | Mistral Large 2's training focused on minimizing hallucinations. | Pi should avoid hallucinations. |
| Community Support and Documentation Quality | Mistral provides documentation for fine-tuning and other capabilities. | Reverse engineered API available for Inflection AI Personal Intelligence (PI). |
| Price | Not available | Pi and Productivity models: $2.50 per 1M input tokens and $10 per 1M output tokens. |
| Ratings | Not available | Not available |