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.
2 / 5 Models Active
1-Click Preset Multi-Model Stacks (4 Models):
Currently Compared Models:Gemma 4 E2B vs Gemma 4 31B 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 | Google · 2026-04 | Google · 2026-04 |
|---|---|---|
| 1. Official Benchmarks & Capability Scores (Green = Leader) | ||
| Intelligence Index (Composite) | 55 / 100 | 81 / 100 |
| SWE-bench Verified (Agentic Coding) | N/A | 68.5% |
| GPQA Diamond (PhD-Level Science) | N/A | 77% |
| LiveCodeBench (Competitive Coding) | N/A | N/A |
| AIME (Olympiad Competition Math) | N/A | 86% |
| MMLU-Pro (10-Choice Reasoning) | 67.2% | 84.8% |
| HumanEval (Code Synthesis) | 76% | 92.5% |
| Terminal-Bench (Agentic CLI Execution) | N/A | N/A |
| LMSYS Chatbot Arena Elo | 1260 | 1410 |
| 2. Token Pricing, Prompt Cache & Throughput Speed | ||
| Input Price (per 1M tokens) | $0.00 / 1M | $0.00 / 1M |
| Output Price (per 1M tokens) | $0.00 / 1M | $0.00 / 1M |
| Cached Input Price (per 1M tokens) | $0.000 / 1M | $0.000 / 1M |
| Blended Price (7:2:1 Cached Workload) | $0.00 / 1M | $0.00 / 1M |
| Context Window Capacity | 131K tokens | 262K tokens |
| Max Output Tokens | 8K tokens | 33K tokens |
| Output Speed (Tokens / sec) | 260 tok/s | 80 tok/s |
| Time to First Token (TTFT Latency) | 0.18s (180 ms) | 0.48s (480 ms) |
| 3. Official Provider Release Specs, API Quotas & Long-Context Rules | ||
| Official API Model ID (SDK) | models/gemma-4-e2b | models/gemma-4-31b |
| API Protocol & Endpoint | Google Gemini API (generateContent) + OpenAI-Compatible SDK | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Lifecycle & GA Support Window | 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 | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Free across full context window (only KV-cache VRAM scales) | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Automatic prefix KV-caching in vLLM / SGLang (0 cost) |
| 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) | 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 |
| Web Search Grounding & Code Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 67 GB VRAM (Native BF16) |
| Supported Inference Engines | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI | vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI |
| Safety & Frontier Classification | Google DeepMind Frontier Safety Framework Verified | Google DeepMind Frontier Safety Framework Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Architecture & Weights License | Ultra-compact edge transformer · Open Weights (Self-Hostable) | Dense open reasoning transformer with native thinking · Open Weights (Self-Hostable) |
Interactive AI Model Comparator
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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.