Head-to-Head Model Comparison

Falcon 3 180B vs Phi-4 Multimodal

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Falcon 3 180BProfile

Phi-4 MultimodalProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

TII

Falcon 3 180B

Modello Base a Pesi Aperti

Falcon 3 180B di TII è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 33K, velocità di 50 token/s, indice di intelligenza di 78/100 e tari

Intelligence Index78 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

Microsoft

Phi-4 Multimodal

IA Multimodale Nativa

Phi-4 Multimodal di Microsoft è un modello di IA progettato per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, con finestra di contesto da 128K, velocità di 160 token/s, indice di intelligenza di 75

Intelligence Index75 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

Both models cost the same under this workload — choose on capability, not price.
Phi-4 Multimodal has a larger context window (128K vs 33K tokens).
Phi-4 Multimodal is faster at 160 tok/s vs 50 tok/s.

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

Feature	Falcon 3 180B	Phi-4 Multimodal
Intelligence Index Composite reasoning & knowledge score (0-100)	78	75
Provider	TII	Microsoft
Input Price Cost per million input tokens	$0.00 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.00 / 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	8K
Throughput Speed Tokens generated per second	50 tok/s	160 tok/s
SWE-bench Verified Real-world software engineering	N/A	N/A
GPQA Diamond Graduate-level reasoning	54%	N/A

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

Phi-4 Multimodal

+220% faster generation

Context

Phi-4 Multimodal

128K tokens window

Punteggi Benchmark Verificati

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

Falcon 3 180BPhi-4 Multimodal

GPQA Diamond (Doctorate-Level Science & Math)

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

54%vsN/A

MMLU-Pro (Multi-task Language Understanding)

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

76%vs71%

LMSYS Chatbot Arena Elo

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

1280ptsvs1250pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

50 tok/s vs160 tok/s

Latenza e Tempo di Risposta

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

Phi-4 Multimodal0.23s

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

Falcon 3 180B10.71s

Phi-4 Multimodal3.35s

Simulatore Interattivo dei Costi Token

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)

Falcon 3 180B Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Phi-4 Multimodal Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

These models cost the same under this workload — no savings either way.Break-even

Falcon 3 180B · Strengths & Key Advantages

Finestra di contesto da 33K con capacità massima di output fino a 4K token (GPQA Diamond 54% · MMLU-Pro 76%)
Throughput elevato di 50 token/secondo con latenza al primo token (TTFT) di soli 710 ms
Pesi aperti (180B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Phi-4 Multimodal · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 8K token (MMLU-Pro 71% · Arena Elo 1250)
Throughput elevato di 160 token/secondo con latenza al primo token (TTFT) di soli 230 ms
Pesi aperti (5.6B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

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

Metric	Falcon 3 180B	Phi-4 Multimodal
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	15K	10K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Falcon 3 180B	Phi-4 Multimodal
Official API Model ID (SDK)	falcon-3-180b	phi-4-multimodal
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2024-12	2025-02
Knowledge Cutoff	September 2024	November 2024
Architecture	High-Scale Dense Open Transformer	Compact Tri-Modal Foundation Transformer
Parameters	180B	5.6B
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)
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) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
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) · 3 GB VRAM (4-bit Quantized) · 12 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, vision, audio
Output Modalities	text	text

Falcon 3 180B vs Phi-4 Multimodal: Risposte Rapide (FAQ)

Which is more intelligent, Falcon 3 180B or Phi-4 Multimodal?

Falcon 3 180B is more intelligent. It scores 78 compared with 75 on the composite Intelligence Index.

Which model is faster?

Phi-4 Multimodal is faster, generating 160 tokens per second compared with 50 tokens per second.

Which model has lower latency?

Phi-4 Multimodal has lower latency, with a time to first token of 0.23s compared with 0.71s.

Which model has a larger context window?

Phi-4 Multimodal has a larger context window, supporting 128K tokens compared with 32.8K tokens.

Verdetto

Sia Falcon 3 180B (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) sia Phi-4 Multimodal (Ideale per la comprensione multimodale nativa di testo e immagini e l’analisi visiva dei documenti, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Falcon 3 180B guida nei benchmark di ragionamento e programmazione, Phi-4 Multimodal garantisce una generazione più rapida e Falcon 3 180B offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Falcon 3 180B o Phi-4 Multimodal?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Falcon 3 180B. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Falcon 3 180B e Phi-4 Multimodal?+

Falcon 3 180B costa $0.00 / $0.00 per milione di token di input/output, mentre Phi-4 Multimodal costa $0.00 / $0.00. Nel costo combinato, Falcon 3 180B risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Falcon 3 180B supporta 32.8K token di contesto contro 128K token di Phi-4 Multimodal, mentre Phi-4 Multimodal offre una velocità di generazione superiore.

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)

Falcon 3 180B vs Phi-4 Multimodal

Cambia e Confronta Qualsiasi Modello

Falcon 3 180B

Phi-4 Multimodal

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Falcon 3 180B · Strengths & Key Advantages

Considerations & Trade-offs

Phi-4 Multimodal · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Falcon 3 180B vs Phi-4 Multimodal: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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