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.
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.
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 | OpenAI · 2026-09 | DeepSeek · 2026-09 |
|---|---|---|
| 1. Official Benchmarks & Capability Scores (Green = Leader) | ||
| Intelligence Index (Composite) | 67 / 100 | 58 / 100 |
| SWE-bench Verified (Agentic Coding) | 70.5% | 74.2% |
| GPQA Diamond (PhD-Level Science) | 73.5% | 90.9% |
| LiveCodeBench (Competitive Coding) | 68% | 73% |
| AIME (Olympiad Competition Math) | 90.2% | 92.4% |
| MMLU-Pro (10-Choice Reasoning) | 86% | 89.5% |
| HumanEval (Code Synthesis) | 94.6% | 96.5% |
| Terminal-Bench (Agentic CLI Execution) | 44% | 31.2% |
| LMSYS Chatbot Arena Elo | 1405 | 1455 |
| 2. Token Pricing, Prompt Cache & Throughput Speed | ||
| Input Price (per 1M tokens) | $0.10 / 1M | $0.30 / 1M |
| Output Price (per 1M tokens) | $0.50 / 1M | $1.20 / 1M |
| Cached Input Price (per 1M tokens) | $0.010 / 1M | $0.006 / 1M |
| Blended Price (7:2:1 Cached Workload) | $0.08 / 1M | $0.18 / 1M |
| Context Window Capacity | 272K tokens | 1M tokens |
| Max Output Tokens | 128K tokens | 384K tokens |
| Output Speed (Tokens / sec) | 245 tok/s | 110 tok/s |
| Time to First Token (TTFT Latency) | 0.38s (380 ms) | 0.46s (460 ms) |
| 3. Official Provider Release Specs, API Quotas & Long-Context Rules | ||
| Official API Model ID (SDK) | gpt-6-luna | deepseek-reasoner |
| API Protocol & Endpoint | OpenAI Responses API & Chat Completions v1 | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Lifecycle & GA Support Window | Active GA (Guaranteed support through 2028+) | Active GA (Guaranteed support through 2028+) |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.1/1M in) across full 272K window | Flat rate ($0.3/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.01/1M (no extra cache-write fee) | Automatic prefix caching at $0.006/1M (no extra cache-write fee) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | 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 | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 |
| Web Search Grounding & Code Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 473 GB VRAM (4-bit Quantized) · 1640 GB VRAM (Native BF16) |
| Supported Inference Engines | Managed OpenAI Cloud API | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Architecture & Weights License | Ultra-budget compact reasoning model · Proprietary API | Causal Encoder-Decoder (20 enc + 20 dec layers) · Open Weights (Self-Hostable) |
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.