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:DeepSeek V4.1-Flash vs GLM-5.2 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 | DeepSeek · 2026-09 | Zhipu AI · 2026-06 |
|---|---|---|
| 1. Official Benchmarks & Capability Scores (Green = Leader) | ||
| Intelligence Index (Composite) | 58 / 100 | 91 / 100 |
| SWE-bench Verified (Agentic Coding) | 74.2% | 67.5% |
| GPQA Diamond (PhD-Level Science) | 90.9% | 73.5% |
| LiveCodeBench (Competitive Coding) | 73% | N/A |
| AIME (Olympiad Competition Math) | 92.4% | N/A |
| MMLU-Pro (10-Choice Reasoning) | 89.5% | 87% |
| HumanEval (Code Synthesis) | 96.5% | 96% |
| Terminal-Bench (Agentic CLI Execution) | 31.2% | N/A |
| LMSYS Chatbot Arena Elo | 1455 | 1440 |
| 2. Token Pricing, Prompt Cache & Throughput Speed | ||
| Input Price (per 1M tokens) | $0.30 / 1M | $0.00 / 1M |
| Output Price (per 1M tokens) | $1.20 / 1M | $0.00 / 1M |
| Cached Input Price (per 1M tokens) | $0.006 / 1M | $0.000 / 1M |
| Blended Price (7:2:1 Cached Workload) | $0.18 / 1M | $0.00 / 1M |
| Context Window Capacity | 1M tokens | 1M tokens |
| Max Output Tokens | 384K tokens | 32K tokens |
| Output Speed (Tokens / sec) | 110 tok/s | 60 tok/s |
| Time to First Token (TTFT Latency) | 0.46s (460 ms) | 0.65s (650 ms) |
| 3. Official Provider Release Specs, API Quotas & Long-Context Rules | ||
| Official API Model ID (SDK) | deepseek-reasoner | glm-5-2 |
| API Protocol & Endpoint | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | 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) | 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) | Flat rate ($0.3/1M in) across full 1000K window | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.006/1M (no extra cache-write fee) | 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) |
| 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) | 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| 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) · 473 GB VRAM (4-bit Quantized) · 1640 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 217 GB VRAM (4-bit Quantized) · 753 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 | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| 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 | Causal Encoder-Decoder (20 enc + 20 dec layers) · Open Weights (Self-Hostable) | Massive Million-Token Open MoE Frontier Transformer · Open Weights (Self-Hostable) |
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.