Head-to-Head Model Comparison

Aya Expanse 32B vs Llama 3.2 90B Vision

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.

Aya Expanse 32BProfile

Llama 3.2 90B VisionProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Cohere

Aya Expanse 32B

Modello Multilingue Globale

Aya Expanse 32B di Cohere è un modello di IA progettato per la traduzione multilingue ad alta precisione e la comunicazione aziendale globale, con finestra di contesto da 128K, velocità di 85 token/s, indice di intelligenza di 44/100 e tari

Intelligence Index44 / 100

Input Token:

$0.25 / 1M

Output Token:

$0.50 / 1M

Context Window:

128K tokens

SWE-bench Verified:

33.5%

Llama 3.2 90B Vision

IA Multimodale Nativa

Llama 3.2 90B Vision di Meta 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 75 token/s, indice di intelligenza di 44/1

Intelligence Index44 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

28.5%

Differenze Chiave a Colpo d’Occhio

Llama 3.2 90B Vision is 1.0x cheaper for API usage (input + output tokens combined).
Aya Expanse 32B is faster at 85 tok/s vs 75 tok/s.
Aya Expanse 32B leads on SWE-bench coding (33.5% vs 28.5%).

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

Feature	Aya Expanse 32B	Llama 3.2 90B Vision
Intelligence Index Composite reasoning & knowledge score (0-100)	44	44
Provider	Cohere	Meta
Input Price Cost per million input tokens	$0.25 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.50 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.14 / 1M	$0.00 / 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	8K
Throughput Speed Tokens generated per second	85 tok/s	75 tok/s
SWE-bench Verified Real-world software engineering	33.5%	28.5%
GPQA Diamond Graduate-level reasoning	50%	48.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.06 / 1M	$0.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Aya Expanse 32B

+5.0% SWE-bench lead

Cost

Llama 3.2 90B Vision

1.0x cheaper monthly runtime

Speed

Aya Expanse 32B

+13% faster generation

Context

Tied

128K tokens window

Punteggi Benchmark Verificati

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

Aya Expanse 32BLlama 3.2 90B Vision

SWE-bench Verified (Autonomous Coding)

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

33.5%vs28.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

50%vs48.2%

MMLU-Pro (Multi-task Language Understanding)

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

73%vs73.5%

LMSYS Chatbot Arena Elo

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

1265ptsvs1260pts

Long-Context Reasoning

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

72%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs75 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

Aya Expanse 32B0.44s

Llama 3.2 90B Vision0.58s

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

Aya Expanse 32B6.32s

Llama 3.2 90B Vision7.25s

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)

Aya Expanse 32B Monthly API Bill

$0.92 / month

$0.25/1M in · $0.5/1M out

Llama 3.2 90B Vision Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Llama 3.2 90B Vision saves approximately $0.92 / month (100%) under this workload.1.0x Savings

Aya Expanse 32B · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 33.5% · GPQA Diamond 50%)
Throughput elevato di 85 token/secondo con latenza al primo token (TTFT) di soli 440 ms
Pesi aperti (32B) 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

Llama 3.2 90B Vision · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 28.5% · GPQA Diamond 48.2%)
Throughput elevato di 75 token/secondo con latenza al primo token (TTFT) di soli 580 ms
Pesi aperti (90B) 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	Aya Expanse 32B	Llama 3.2 90B Vision
Cost per Task Estimated USD to finish one task	$0.18	$0.20
Output Tokens / Task Tokens generated per task	28K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Aya Expanse 32B	Llama 3.2 90B Vision
Official API Model ID (SDK)	aya-expanse-32b	meta-llama/Llama-3.2-90B-Vision
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2024-10	2024-09
Knowledge Cutoff	August 2024	December 2023
Architecture	High-Capacity Multilingual Transformer	Multimodal Adapter-Fused GQA Transformer
Parameters	32B	90B
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 ($0.25/1M in) across full 128K window	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Cached input at $0.06/1M tokens	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)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 56 GB VRAM (4-bit Quantized) · 194 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
Output Modalities	text	text

Aya Expanse 32B vs Llama 3.2 90B Vision: Risposte Rapide (FAQ)

Which model is faster?

Aya Expanse 32B is faster, generating 85 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Llama 3.2 90B Vision is cheaper at $0.00 per 1M tokens blended, compared with $0.14 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Aya Expanse 32B has lower latency, with a time to first token of 0.44s compared with 0.58s.

Verdetto

Sia Aya Expanse 32B (Ideale per la traduzione multilingue ad alta precisione e la comunicazione aziendale globale, sistemi RAG aziendali e integrazioni API scalabili.) sia Llama 3.2 90B Vision (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: Aya Expanse 32B guida nei benchmark di ragionamento e programmazione, Aya Expanse 32B garantisce una generazione più rapida e Llama 3.2 90B Vision offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Aya Expanse 32B o Llama 3.2 90B Vision?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Aya Expanse 32B. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Aya Expanse 32B e Llama 3.2 90B Vision?+

Aya Expanse 32B costa $0.25 / $0.50 per milione di token di input/output, mentre Llama 3.2 90B Vision costa $0.00 / $0.00. Nel costo combinato, Llama 3.2 90B Vision risulta più economico.

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

Aya Expanse 32B supporta 128K token di contesto contro 128K token di Llama 3.2 90B Vision, mentre Aya Expanse 32B 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)

Aya Expanse 32B vs Llama 3.2 90B Vision

Cambia e Confronta Qualsiasi Modello

Aya Expanse 32B

Llama 3.2 90B Vision

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Aya Expanse 32B · Strengths & Key Advantages

Considerations & Trade-offs

Llama 3.2 90B Vision · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Aya Expanse 32B vs Llama 3.2 90B Vision: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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