Head-to-Head Model Comparison

Phi-4 Multimodal vs Command R7B Arabic

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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Phi-4 MultimodalProfile

Command R7B ArabicProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Microsoft

Phi-4 Multimodal

AI Multimodal Asli

Phi-4 Multimodal dari Microsoft adalah model AI yang dirancang untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, menghadirkan jendela konteks 128K, kecepatan 160 token/detik, indeks kecerdasan 75/100, serta ak

Intelligence Index75 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Cohere

Command R7B Arabic

Model Dasar Bobot Terbuka

Command R7B Arabic dari Cohere adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 135 token/detik, indeks kecerdasan 39/100, serta tarif

Intelligence Index39 / 100

Input Token:

$0.07 / 1M

Output Token:

$0.20 / 1M

Context Window:

128K tokens

SWE-bench Verified:

26%

Perbedaan Utama Sekilas

Phi-4 Multimodal is 1.0x cheaper for API usage (input + output tokens combined).
Phi-4 Multimodal is faster at 160 tok/s vs 135 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Phi-4 Multimodal	Command R7B Arabic
Intelligence Index Composite reasoning & knowledge score (0-100)	75	39
Provider	Microsoft	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	128K tokens~192 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	4K
Throughput Speed Tokens generated per second	160 tok/s	135 tok/s
SWE-bench Verified Real-world software engineering	N/A	26%
GPQA Diamond Graduate-level reasoning	N/A	43%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.02 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Phi-4 Multimodal

1.0x cheaper monthly runtime

Speed

Phi-4 Multimodal

+19% faster generation

Context

Tied

128K tokens window

Skor Benchmark Terverifikasi

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

Phi-4 MultimodalCommand R7B Arabic

SWE-bench Verified (Autonomous Coding)

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

N/Avs26%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs43%

MMLU-Pro (Multi-task Language Understanding)

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

71%vs67%

LMSYS Chatbot Arena Elo

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

1250ptsvs1225pts

Long-Context Reasoning

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

N/Avs70%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs135 tok/s

Latensi & Waktu Respons

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

Phi-4 Multimodal0.23s

Command R7B Arabic0.31s

Est. End-to-End Response (500 tokens)TTFT + generation time

Phi-4 Multimodal3.35s

Command R7B Arabic4.01s

Simulator Biaya Token Interaktif

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Phi-4 Multimodal Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Command R7B Arabic Monthly API Bill

$0.32 / month

$0.07/1M in · $0.2/1M out

Phi-4 Multimodal saves approximately $0.32 / month (100%) under this workload.1.0x Savings

Phi-4 Multimodal · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (MMLU-Pro 71% · Arena Elo 1250)
Kecepatan generasi tinggi 160 token/detik dengan latensi token pertama (TTFT) hanya 230 ms
Bobot terbuka (5.6B) 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 Arabic · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 4K token (SWE-bench Verified 26% · GPQA Diamond 43%)
Kecepatan generasi tinggi 135 token/detik dengan latensi token pertama (TTFT) hanya 310 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	Phi-4 Multimodal	Command R7B Arabic
Cost per Task Estimated USD to finish one task	$0.00	$0.05
Output Tokens / Task Tokens generated per task	10K	20K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Phi-4 Multimodal	Command R7B Arabic
Official API Model ID (SDK)	phi-4-multimodal	command-r7b-arabic
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-02	2025-02
Knowledge Cutoff	November 2024	December 2024
Architecture	Compact Tri-Modal Foundation Transformer	Arabic-Specialized RAG Transformer
Parameters	5.6B	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) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 3 GB VRAM (4-bit Quantized) · 12 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, vision, audio	text
Output Modalities	text	text

Phi-4 Multimodal vs Command R7B Arabic: Jawaban Cepat (FAQ)

Which is more intelligent, Phi-4 Multimodal or Command R7B Arabic?

Phi-4 Multimodal is more intelligent. It scores 75 compared with 39 on the composite Intelligence Index.

Which model is faster?

Phi-4 Multimodal is faster, generating 160 tokens per second compared with 135 tokens per second.

Which model is cheaper to run?

Phi-4 Multimodal 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?

Phi-4 Multimodal has lower latency, with a time to first token of 0.23s compared with 0.31s.

Kesimpulan

Baik Phi-4 Multimodal (Sangat cocok untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Command R7B Arabic (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Phi-4 Multimodal unggul dalam penalaran dan pemrograman, Phi-4 Multimodal memberikan kecepatan generasi token lebih tinggi, dan Phi-4 Multimodal lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Phi-4 Multimodal atau Command R7B Arabic?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Phi-4 Multimodal memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Phi-4 Multimodal vs Command R7B Arabic?+

Phi-4 Multimodal mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Command R7B Arabic sebesar $0.07 / $0.20. Secara keseluruhan, Phi-4 Multimodal lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Phi-4 Multimodal mendukung konteks 128K token dibandingkan 128K token pada Command R7B Arabic, sementara Phi-4 Multimodal unggul dalam kecepatan output token per detik.

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 & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Phi-4 Multimodal vs Command R7B Arabic

Ganti & Bandingkan Model Apa Saja

Phi-4 Multimodal

Command R7B Arabic

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Phi-4 Multimodal · Strengths & Key Advantages

Considerations & Trade-offs

Command R7B Arabic · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Phi-4 Multimodal vs Command R7B Arabic: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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