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Head-to-Head Model Comparison

Falcon 3 180B vs Command R7B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Falcon 3 180B vs Command R7B: Benchmarks, Pricing & Speed Comparison

TII 的 Falcon 3 180B 与 Cohere 的 Command R7B 是当前备受关注的两款主力 AI 模型。Falcon 3 180B 提供 32.8K Token 上下文窗口，API 定价为每百万 Token 输入 $0.00 / 输出 $0.00；而 Command R7B 提供 128K Token 上下文窗口，定价为每百万 Token 输入 $0.07 / 输出 $0.20。以下为两者的基准测试、延迟与成本全面对比。

模型直接对比 (VS)

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TII

Falcon 3 180B

开源权重基础大模型

TII 推出的 Falcon 3 180B 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型，具备 33K 上下文窗口、50 Token/秒生成速度与 78/100 综合智能指数（免费开源权重）。

Intelligence Index78 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

Cohere

Command R7B

开源权重基础大模型

Cohere 推出的 Command R7B 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型，具备 128K 上下文窗口、140 Token/秒生成速度与 38/100 综合智能指数（每百万 Token $0.07 输入 / $0.2 输出）。

Intelligence Index38 / 100
Input Token:

$0.07 / 1M

Output Token:

$0.20 / 1M

Context Window:

128K tokens

SWE-bench Verified:

27%

核心差异一览

  • Falcon 3 180B is 1.0x cheaper for API usage (input + output tokens combined).
  • Command R7B has a larger context window (128K vs 33K tokens).
  • Command R7B is faster at 140 tok/s vs 50 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureFalcon 3 180BCommand R7B
Intelligence Index
Composite reasoning & knowledge score (0-100)
7838
Provider
TIICohere
Input Price
Cost per million input tokens
$0.00 / 1M$0.07 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$0.20 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$0.05 / 1M
Context Window
Maximum input + output tokens
32.8K tokens~49 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
50 tok/s140 tok/s
SWE-bench Verified
Real-world software engineering
N/A27%
GPQA Diamond
Graduate-level reasoning
54%42.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.02 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Falcon 3 180B
1.0x cheaper monthly runtime
Speed
Command R7B
+180% faster generation
Context
Command R7B
128K tokens window

权威基准测试得分对比

Official evaluation metrics verified by independent third-party research labs.

Falcon 3 180BCommand R7B
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs27%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

54%vs42.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

76%vs66%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1280ptsvs1215pts
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs68%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

50 tok/s vs140 tok/s

延迟与响应速度

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Falcon 3 180B0.71s
Command R7B0.29s
Est. End-to-End Response (500 tokens)TTFT + generation time
Falcon 3 180B10.71s
Command R7B3.86s

实时 Token 成本模拟器

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Falcon 3 180B Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Command R7B Monthly API Bill
$0.32 / month
$0.07/1M in · $0.2/1M out
Falcon 3 180B saves approximately $0.32 / month (100%) under this workload.1.0x Savings

Falcon 3 180B · Strengths & Key Advantages

  • 提供 33K 上下文窗口与最高 4K 输出容量，核心基准表现优异（GPQA Diamond 54% · MMLU-Pro 76%）
  • 高达 50 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 710 毫秒
  • 开放模型权重 (180B)，支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

Command R7B · Strengths & Key Advantages

  • 提供 128K 上下文窗口与最高 4K 输出容量，核心基准表现优异（SWE-bench Verified 27% · GPQA Diamond 42.5%）
  • 高达 140 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 290 毫秒
  • 开放模型权重 (7B)，支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricFalcon 3 180BCommand R7B
Cost per Task
Estimated USD to finish one task
$0.00$0.05
Output Tokens / Task
Tokens generated per task
15K20K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureFalcon 3 180BCommand R7B
Official API Model ID (SDK)falcon-3-180bcommand-r7b
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2024-122024-12
Knowledge CutoffSeptember 2024October 2024
ArchitectureHigh-Scale Dense Open TransformerEfficient Compact RAG Transformer
Parameters180B7B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (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)Flat rate ($0.07/1M in) across full 128K window
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)Cached input at $0.02/1M tokens
Computer Use / GUI AgentAPI / 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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 112 GB VRAM (4-bit Quantized) · 387 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 4 GB VRAM (4-bit Quantized) · 15 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

Falcon 3 180B vs Command R7B: 常见问题解答 (FAQ)

Which is more intelligent, Falcon 3 180B or Command R7B?

Falcon 3 180B is more intelligent. It scores 78 compared with 38 on the composite Intelligence Index.

Which model is faster?

Command R7B is faster, generating 140 tokens per second compared with 50 tokens per second.

Which model is cheaper to run?

Falcon 3 180B is cheaper at $0.00 per 1M tokens blended, compared with $0.05 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Command R7B has lower latency, with a time to first token of 0.29s compared with 0.71s.

Which model has a larger context window?

Command R7B has a larger context window, supporting 128K tokens compared with 32.8K tokens.

综合结论

综合来看，Falcon 3 180B（适合：支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 Command R7B（适合：支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：Falcon 3 180B 在综合智能与编程基准测试中表现更强，Command R7B 拥有更快的 Token 生成速度，而 Falcon 3 180B 则在规模化 API 部署中具备更高的成本效益。

常见问题 (FAQ)

在编程和深度推理方面，Falcon 3 180B 和 Command R7B 哪个更强？+

在综合智能指数与编程基准评测中，Falcon 3 180B 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。

Falcon 3 180B 与 Command R7B 的 API 价格哪个更便宜？+

Falcon 3 180B 的 API 价格为输入 $0.00 / 输出 $0.00（每百万 Token），Command R7B 为输入 $0.07 / 输出 $0.20。综合混合成本来看，Falcon 3 180B 更具性价比。

哪款模型拥有更大的上下文窗口和更快的响应速度？+

Falcon 3 180B 支持 32.8K Token 上下文窗口，而 Command R7B 支持 128K Token。在流式生成速度方面，Command R7B 的吞吐表现更快。

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

数据来源: TII 与 Cohere 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。