Multi-Model AI Comparator (2-4 Models)
Compare any 2 to 4 frontier AI models side by side across Intelligence Index, coding & reasoning benchmarks, API token pricing, context window, and inference speed.
Multi-Model Benchmark & Official Release Intelligence Matrix
Compare Up to 5 AI Models Side-by-Side on One Page
Evaluate benchmark scores, token pricing, speed, and official provider release specs (API Model ID, Rate Limits, Computer Use, MCP, VRAM & ZDR Compliance) side by side.
4 / 5 Models Active
1-Click Preset Multi-Model Stacks (4 Models):
Currently Compared Models:Codestral vs Gemini 4 Argon Arena
Intelligence vs Blended Price (7:2:1)
Top-left quadrant delivers the highest intelligence per dollar
Intelligence vs Output Speed (tok/s)
Top-right quadrant delivers both frontier intelligence and real-time throughput
| Benchmark / Official Specification | Mistral AI · 2024-05 | Google · 2026-09 | OpenAI · 2026-09 | Anthropic · 2026-09 |
|---|---|---|---|---|
| 1. Official Benchmarks & Capability Scores (Green = Leader) | ||||
| Intelligence Index (Composite) | 40 / 100 | 97 / 100 | 96 / 100 | 94 / 100 |
| SWE-bench Verified (Agentic Coding) | 28% | 81.9% | 82.4% | 84.6% |
| GPQA Diamond (PhD-Level Science) | 42% | 81.5% | 80.9% | 82.3% |
| LiveCodeBench (Competitive Coding) | N/A | 80.5% | 79.8% | 83.1% |
| AIME (Olympiad Competition Math) | N/A | 94.8% | 93.6% | 95.4% |
| MMLU-Pro (10-Choice Reasoning) | 70% | 90.8% | 89.9% | 91.5% |
| HumanEval (Code Synthesis) | 81.1% | 97.2% | 97.8% | 98.4% |
| Terminal-Bench (Agentic CLI Execution) | N/A | 57.4% | 63.8% | 66.4% |
| LMSYS Chatbot Arena Elo | 1240 | 1525 | 1520 | 1507 |
| 2. Token Pricing, Prompt Cache & Throughput Speed | ||||
| Input Price (per 1M tokens) | $0.20 / 1M | $2.00 / 1M | $10.00 / 1M | $4.00 / 1M |
| Output Price (per 1M tokens) | $0.60 / 1M | $10.00 / 1M | $50.00 / 1M | $20.00 / 1M |
| Cached Input Price (per 1M tokens) | $0.050 / 1M | $0.100 / 1M | $1.000 / 1M | $0.400 / 1M |
| Blended Price (7:2:1 Cached Workload) | $0.14 / 1M | $1.47 / 1M | $7.70 / 1M | $3.08 / 1M |
| Context Window Capacity | 256K tokens | 1M tokens | 272K tokens | 1M tokens |
| Max Output Tokens | 8K tokens | 1M tokens | 128K tokens | 128K tokens |
| Output Speed (Tokens / sec) | 110 tok/s | 115 tok/s | 100 tok/s | 78 tok/s |
| Time to First Token (TTFT Latency) | 0.35s (350 ms) | 0.85s (850 ms) | 0.95s (950 ms) | 1.40s (1400 ms) |
| 3. Official Provider Release Specs, API Quotas & Long-Context Rules | ||||
| Official API Model ID (SDK) | codestral-latest | models/gemini-4-argon | gpt-6-astra | claude-opus-5-5-20260901 |
| API Protocol & Endpoint | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Lifecycle & GA Support Window | Legacy Stable (Upgrade path available in Mistral AI lineup) | Active GA (Guaranteed support through 2028+) | Active GA (Guaranteed support through 2028+) | Active GA (Guaranteed support through 2028+) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.2/1M in) across full 256K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($10/1M in) across full 272K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL | Automatic prefix caching at $1/1M (no extra cache-write fee) | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 4. Agentic Capabilities, Self-Hosting VRAM & Enterprise Compliance | ||||
| Computer Use / Browser GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Code Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Vertex AI Supervised Adapter Tuning & Context Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 14 GB VRAM (4-bit Quantized) · 47 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Supported Inference Engines | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI | Managed Google Cloud API | Managed OpenAI Cloud API | Managed Anthropic Cloud API |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Google DeepMind Frontier Safety Framework Verified | OpenAI Preparedness Framework Audited & System Card Published | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Architecture & Weights License | Code-Optimized Transformer with 32K Window · Open Weights (Self-Hostable) | Pathways Multimodal Sparse Mixture-of-Experts · Proprietary API | Omni-Adaptive Autoregressive with Dynamic CoT · Proprietary API | Extended Autonomous Hybrid Reasoning Transformer · Proprietary API |
Interactive AI Model Comparator
Compare Any Two AI Models Head-to-Head
Select any two models across 33 global AI labs (Google, OpenAI, Anthropic, xAI, Meta, DeepSeek, Alibaba Qwen, Mistral & more) to evaluate token economics, speed, benchmarks, and context.
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.