Falcon 3 180B vs Command R7B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Falcon 3 180B dari TII dan Command R7B dari Cohere adalah dua model AI unggulan. Falcon 3 180B menawarkan jendela konteks 32.8K token dengan harga $0.00/$0.00 per 1 juta token, sedangkan Command R7B menyediakan konteks 128K token seharga $0.07/$0.20 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Falcon 3 180B
Model Dasar Bobot TerbukaFalcon 3 180B dari TII adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 33K, kecepatan 50 token/detik, indeks kecerdasan 78/100, serta akses gratis ope
$0.00 / 1M
$0.00 / 1M
32.8K tokens
N/A
Command R7B
Model Dasar Bobot TerbukaCommand R7B dari Cohere adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 140 token/detik, indeks kecerdasan 38/100, serta tarif $0.07/$
$0.07 / 1M
$0.20 / 1M
128K tokens
27%
Perbedaan Utama Sekilas
- 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.
| Feature | Falcon 3 180B | Command R7B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 78 | 38 |
Provider | TII | Cohere |
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 text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 4K | 4K |
Throughput Speed Tokens generated per second | 50 tok/s | 140 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 27% |
GPQA Diamond Graduate-level reasoning | 54% | 42.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.02 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Falcon 3 180B · Strengths & Key Advantages
- Jendela konteks 33K dengan kapasitas output maksimum hingga 4K token (GPQA Diamond 54% · MMLU-Pro 76%)
- Kecepatan generasi tinggi 50 token/detik dengan latensi token pertama (TTFT) hanya 710 ms
- Bobot terbuka (180B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Command R7B · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 4K token (SWE-bench Verified 27% · GPQA Diamond 42.5%)
- Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 290 ms
- Bobot terbuka (7B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Falcon 3 180B | Command R7B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.00 | $0.05 |
Output Tokens / Task Tokens generated per task | 15K | 20K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Falcon 3 180B | Command R7B |
|---|---|---|
| Official API Model ID (SDK) | falcon-3-180b | command-r7b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2024-12 | 2024-12 |
| Knowledge Cutoff | September 2024 | October 2024 |
| Architecture | High-Scale Dense Open Transformer | Efficient Compact RAG Transformer |
| Parameters | 180B | 7B |
| 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) | Flat rate ($0.07/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Cached input at $0.02/1M tokens |
| Computer Use / 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 & 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) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / 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 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 |
| Input Modalities | text | text |
| Output Modalities | text | text |
Falcon 3 180B vs Command R7B: Jawaban Cepat (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.
Kesimpulan
Baik Falcon 3 180B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Command R7B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Falcon 3 180B unggul dalam penalaran dan pemrograman, Command R7B memberikan kecepatan generasi token lebih tinggi, dan Falcon 3 180B lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Falcon 3 180B atau Command R7B?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Falcon 3 180B memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Falcon 3 180B vs Command R7B?+
Falcon 3 180B mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Command R7B sebesar $0.07 / $0.20. Secara keseluruhan, Falcon 3 180B lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Falcon 3 180B mendukung konteks 32.8K token dibandingkan 128K token pada Command R7B, sementara Command R7B unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sumber resmi: Dokumentasi API resmi TII & Cohere serta evaluasi benchmark independen (2026).