At a glance
OpenAI
Specifications
All values are in tokens and come from each model’s page on developers.openai.com. All of these models take text and image input and produce text output.
GPT 5.6 Sol
gpt-5.6-sol · Official docs · Launch announcement
OpenAI’s “GPT-5.6 flagship model for complex professional work”. OpenAI positions Sol for “frontier reasoning and long-horizon agentic work”.
GPT 5.6 Terra
gpt-5.6-terra · Official docs · Launch announcement
A “GPT-5.6 model that balances intelligence and cost”. OpenAI says it has “GPT-5.5-competitive performance at 2x lower cost”.
GPT 5.6 Luna
gpt-5.6-luna · Official docs · Launch announcement
A “GPT-5.6 model optimized for cost-sensitive workloads”, designed for high-volume use. OpenAI calls it “the fastest, most affordable member of the family”.
OpenAI publishes its GPT-5.6 capability benchmarks (such as Terminal-Bench 2.1) as charts in the launch announcement. The Third-party figures above are published by Artificial Analysis, an independent benchmarking company, not by OpenAI. Accessed October 16, 2026.
GPT 5.4
gpt-5.4 · Official docs · Launch announcement with benchmarks
OpenAI describes GPT-5.4 as “a flagship model for complex professional work” and “a more affordable model for coding and professional work”.
GPT 5.4 mini
gpt-5.4-mini · Official docs · Launch announcement with benchmarks
“Our strongest mini model yet for coding, computer use, and subagents”. OpenAI says it brings GPT-5.4’s strengths to a faster, more efficient model for high-volume workloads.
GPT 5.4 nano
gpt-5.4-nano · Official docs · Launch announcement with benchmarks
“Our cheapest GPT-5.4-class model for simple high-volume tasks”, such as classification, data extraction, ranking and sub-agents.
GPT 5
gpt-5 · Official docs · Launch announcement with benchmarks
OpenAI’s “previous intelligent reasoning model for coding and agentic tasks with configurable reasoning effort”. OpenAI now recommends newer models for new projects.
GPT 5 mini
gpt-5-mini · Official docs · Launch announcement with benchmarks
“A faster, more cost-efficient version of GPT-5”, suited to well-defined tasks and precise prompts. For new low-latency, high-volume workloads, OpenAI recommends GPT 5.6 Terra.
GPT 5 nano
gpt-5-nano · Official docs · Launch announcement with benchmarks
The “fastest, most cost-efficient version of GPT-5”, suited to summarization and classification. For new speed- and cost-sensitive workloads, OpenAI recommends GPT 5.6 Luna.
GPT 5.1
gpt-5.1 · Official docs
A “flagship model for coding and agentic tasks with configurable reasoning and non-reasoning effort”.
GPT 5.2
gpt-5.2 · Official docs · Launch announcement with benchmarks
OpenAI’s “previous flagship model for professional work with configurable reasoning effort”.
GPT 4.1 mini
gpt-4.1-mini · Official docs · Launch announcement with benchmarks
A “smaller, faster version of GPT-4.1” that “excels at instruction following and tool calling”. It has “low latency without a reasoning step”.
OpenAI’s model pages don’t list benchmark scores. For GPT 5.4 and earlier, the benchmark results are in the launch announcements linked above. No independent benchmark figures for these versions were available from Artificial Analysis.
Specifications
Token limits and status come from each model’s page on ai.google.dev. Knowledge cutoffs come from the model page or the model card. For Gemini 3.6 Flash and later, Google notes that knowledge in some domains may only go up to January 2025. All Gemini models listed here accept text, image, video and audio input and produce text output.
Gemini 3.8 Flash
gemini-3.8-flash · Official docs · Model card
“Our most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents” and complex enterprise workflows, at Flash speed and cost. Thinking levels: low, medium and high.
Gemini 3.7 Flash
gemini-3.7-flash · Official docs · Model card
A previous-generation model in the Gemini 3 series.
Gemini 3.6 Flash
gemini-3.6-flash · Official docs · Model card
Provides “sustained frontier-level intelligence optimized for real-world tasks at a higher speed and lower cost”.
Gemini 3.5 Flash
gemini-3.5-flash · Official docs · Model card
An earlier-generation Flash model that provided frontier-level intelligence at higher speed and lower cost.
Gemini 3.5 Flash Lite
gemini-3.5-flash-lite · Official docs · Model card
“A low-latency, cost-effective multimodal model optimized for high-throughput, low-cost execution for subagent tasks” and document parsing.
Gemini 3.1 Flash Lite
gemini-3.1-flash-lite · Official docs · Model card
“A low-latency, cost-effective multimodal model optimized for high-frequency, lightweight tasks.” Scores are for the high thinking level.
Gemini 3 Flash
gemini-3-flash-preview · Official docs
Google describes it as “the best model in the world for multimodal understanding, and our most powerful agentic and vibe-coding model yet” (at its December 2025 launch). This model is in preview.
Gemini 3.1 Pro
gemini-3.1-pro-preview · Official docs · Model card
Refines the Gemini 3 Pro series and “provides better thinking, improved token efficiency, and a more grounded, factually consistent experience”. This model is in preview. Scores are for the high thinking level.
Gemini 2.5 Flash
gemini-2.5-flash · Official docs
“Our best model in terms of price-performance, offering well-rounded capabilities.” The Gemini API docs say the 2.5 models are not deprecated, and recommend Gemini 3.5 Flash Lite or Gemini 3.8 Flash for new projects.
Gemma 4
google/gemma-4-31b-it · Model card · Google DeepMind
Gemma 4 is Google DeepMind’s open model family, built from Gemini 3 research and released under the Apache 2.0 license. This is the 31B-parameter instruction-tuned model. It has a 256K-token context window, takes text and image input, and supports function calling and configurable thinking. Google says it supports 35+ languages out of the box and was pre-trained on 140+.
Anthropic
Specifications
All values are in tokens and come from each model’s page in the Claude Platform docs. All of these models take text and image input and produce text output. For language support, see Anthropic’s multilingual support guide.
Claude Opus 5.5
claude-opus-5-5 · Official docs · Announcement
Built “for long-running agentic coding and knowledge work”. Anthropic recommends starting with Claude Opus 5.5 for most workloads. Scores use max effort unless noted.
Claude Sonnet 5.5
claude-sonnet-5-5 · Official docs · Announcement
“The best combination of speed and intelligence.” Anthropic says it runs 30%+ faster and costs up to 30% less for most work than Claude Sonnet 5.
Claude Haiku 5.5
claude-haiku-5-5 · Official docs · Announcement
Built “for high-volume, latency-sensitive tasks such as classification, extraction, and routing”. Anthropic calls it “the cheapest, fastest, and most capable small model we’ve ever released”.
Claude Opus 5
claude-opus-5 · Official docs · Announcement
Anthropic describes Claude Opus 5 as “a thoughtful and proactive model”. Anthropic now lists it as a legacy model and suggests migrating to Claude Opus 5.5.
Claude Sonnet 5
claude-sonnet-5 · Official docs · Announcement
Anthropic describes it as “built to be the most agentic Sonnet model yet”. Anthropic now lists it as a legacy model.
Each provider chooses its own benchmarks, settings (such as reasoning effort) and test conditions, so scores from different providers are not directly comparable. Test candidate models with prompts and conversations from your own use case.