Microsoft AI

Microsoft AI's announced faster MAI voice variant for lower-latency text-to-speech workflows.

Anthropic

Catalog entry for this named release; see the provider’s official documentation for modalities, pricing, and context limits.

Anthropic

Anthropic's most capable generally available Claude model for complex reasoning and agentic coding, documented in the Claude model overview.

OpenAI

OpenAI’s o1 series emphasizes extended internal reasoning before answering—useful for competition-style math, complex debugging, and multi-step planning where latency is acceptable. It behaves differently from standard chat models: tune prompts for chain-of-thought style tasks and measure time-to-first-token.

Mistral AI

Mistral’s frontier-class multilingual model emphasizing JSON adherence, agent-friendly behavior, and competitive reasoning within the Mistral API ecosystem. European teams often evaluate it for GDPR-adjacent deployment patterns alongside US-hosted alternatives.

xAI

Grok-2 is xAI’s flagship chat model positioned for real-time knowledge integrations and high-throughput conversational products on xAI’s API. Availability and pricing evolve—treat capabilities as vendor-specific.

OpenAI

OpenAI’s flagship multimodal chat model for production assistants: native image and audio inputs, strong tool and JSON-mode behavior, and low-latency routing on the Chat Completions API. Teams use it for vision-heavy workflows, agent loops with parallel tools, and structured extraction where schema adherence matters.

Google

Google DeepMind Gemini 1.5 Pro targets long-context multimodal workloads—large effective context for retrieval-heavy document pipelines, plus image, audio, and video inputs on supported surfaces. It is often paired with Vertex AI or the Gemini API for enterprise workloads on GCP.

DeepSeek

DeepSeek-V3 is a large-scale language model family noted for strong coding and math performance under open or research-friendly terms (verify the exact license for your deployment). Teams adopt it for cost-sensitive research, self-hosted inference, or comparison against frontier APIs.

Anthropic

Anthropic’s balanced Sonnet-tier model tuned for long-context reasoning, careful instruction following, and strong performance on coding and analysis workloads. It is a common enterprise choice on the Anthropic API and on AWS Bedrock when teams need large context for RAG and document review.

Microsoft

Phi-3 Medium is a compact instruct model aimed at strong quality per parameter for on-device and cost-sensitive cloud inference. It competes with other SLMs on coding and reasoning benchmarks—validate on your domain prompts.

Mistral AI

Mixtral 8x7B Instruct is a sparse mixture-of-experts open model noted for strong quality per active parameter and efficient inference vs dense models of similar capability. Widely hosted on inference clouds and self-hosted stacks.

Meta

Llama 3.2 3B Instruct is a compact instruct model in Meta’s 3.2 generation aimed at mobile and edge scenarios with multilingual support on supported checkpoints. Verify hardware targets and license terms for your distribution channel.

Meta

Llama 3.2 1B Instruct is among the smallest Llama instruct checkpoints for extreme latency and footprint constraints. Use for routing, tagging, and toy assistants—not for complex reasoning without retrieval augmentation.

xAI

Grok-3 represents xAI’s newer generation aimed at stronger reasoning and tool use versus Grok-2. Capabilities and rollout are version-specific—validate against xAI documentation for your account tier.

OpenAI

GPT-4o mini is a cost-optimized GPT-4o-family model for high-volume chat, moderation, and routing layers where frontier quality is unnecessary. It supports multimodal inputs on supported API surfaces and is often used as a fast first pass before escalating to larger models.

OpenAI

GPT-4 Turbo is a widely deployed GPT-4-class chat model with a large context window on the OpenAI API, aimed at long-document workflows, retrieval bundles, and production assistants that do not require GPT-4o’s multimodal stack. It remains a common baseline for cost/quality tradeoffs.

OpenAI

GPT-3.5 Turbo is a long-standing cost-efficient chat model family on the OpenAI API for simple assistants, classification, and legacy integrations. Many teams still use it for non-critical paths or as a fallback when newer models are rate-limited.

Google

Gemini 1.5 Flash targets low-latency, cost-efficient multimodal chat and retrieval workloads on the Gemini API and Vertex AI. It keeps much of the long-context family behavior with faster responses for interactive apps.

Google

Gemini 1.0 Pro represents Google’s first broadly marketed Gemini-era general model for text and basic multimodal tasks on Vertex and consumer surfaces. New projects should prefer 1.5+ generations unless constrained by legacy integrations—verify availability.

Cohere

Command R is Cohere’s earlier RAG-oriented model line preceding Command R+, focused on grounded generation with connectors and multilingual enterprise search. Useful when comparing tiered Cohere stacks or maintaining legacy integrations.

Anthropic

Claude 3 Opus was Anthropic’s highest-capability Claude 3-era model for difficult reasoning, nuanced writing, and complex analysis before later Sonnet generations. Teams still reference it for historical benchmarks and legacy deployments—verify current availability in API and Bedrock model lists.

Anthropic

Claude 3 Sonnet balanced cost and capability in the Claude 3 generation—useful for general assistants and document workflows where Opus was unnecessary. New deployments should compare against Claude 3.5 Sonnet for pricing and quality.

Anthropic

Claude 3 Haiku is the fast Claude 3-era model for simple tasks and high throughput. Prefer 3.5 Haiku when available for better quality at similar latency targets—confirm SKUs on your cloud path.