Head-to-Head Model Comparison

Aya Vision 32B vs DeepSeek-V3-0324

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 Vision 32BProfile

DeepSeek-V3-0324Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Cohere

Aya Vision 32B

Modello Multilingue Globale

Aya Vision 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 16K, velocità di 75 token/s, indice di intelligenza di 45/100 e tariff

Intelligence Index45 / 100

Input Token:

$0.35 / 1M

Output Token:

$0.80 / 1M

Context Window:

16K tokens

SWE-bench Verified:

32%

DeepSeek

DeepSeek-V3-0324

Modello Base a Pesi Aperti

DeepSeek-V3-0324 di DeepSeek 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 128K, velocità di 65 token/s, indice di intelligenza di 48/1

Intelligence Index48 / 100

Input Token:

$0.27 / 1M

Output Token:

$1.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

52.4%

Differenze Chiave a Colpo d’Occhio

Aya Vision 32B is 1.1x cheaper for API usage (input + output tokens combined).
DeepSeek-V3-0324 has a larger context window (128K vs 16K tokens).
Aya Vision 32B is faster at 75 tok/s vs 65 tok/s.
DeepSeek-V3-0324 leads on SWE-bench coding (52.4% vs 32.0%).

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

Feature	Aya Vision 32B	DeepSeek-V3-0324
Intelligence Index Composite reasoning & knowledge score (0-100)	45	48
Provider	Cohere	DeepSeek
Input Price Cost per million input tokens	$0.35 / 1M	$0.27 / 1M
Output Price Cost per million output tokens	$0.80 / 1M	$1.10 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.21 / 1M	$0.21 / 1M
Context Window Maximum input + output tokens	16K tokens~24 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	75 tok/s	65 tok/s
SWE-bench Verified Real-world software engineering	32%	52.4%
GPQA Diamond Graduate-level reasoning	51.5%	63.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.08 / 1M	$0.07 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

DeepSeek-V3-0324

+20.4% SWE-bench lead

Cost

Aya Vision 32B

1.1x cheaper monthly runtime

Speed

Aya Vision 32B

+15% faster generation

Context

DeepSeek-V3-0324

128K tokens window

Punteggi Benchmark Verificati

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

Aya Vision 32BDeepSeek-V3-0324

SWE-bench Verified (Autonomous Coding)

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

32%vs52.4%

GPQA Diamond (Doctorate-Level Science & Math)

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

51.5%vs63.5%

MMLU-Pro (Multi-task Language Understanding)

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

74%vs78.4%

LMSYS Chatbot Arena Elo

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

1280ptsvs1320pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs10.2%

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs34.8%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs32.1%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs54.8%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs72%

Long-Context Reasoning

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

N/Avs71.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs65 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 Vision 32B0.48s

DeepSeek-V3-03240.65s

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

Aya Vision 32B7.15s

DeepSeek-V3-03248.34s

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 Vision 32B Monthly API Bill

$1.36 / month

$0.35/1M in · $0.8/1M out

DeepSeek-V3-0324 Monthly API Bill

$1.50 / month

$0.27/1M in · $1.1/1M out

Aya Vision 32B saves approximately $0.14 / month (9%) under this workload.1.1x Savings

Aya Vision 32B · Strengths & Key Advantages

Finestra di contesto da 16K con capacità massima di output fino a 4K token (SWE-bench Verified 32% · GPQA Diamond 51.5%)
Throughput elevato di 75 token/secondo con latenza al primo token (TTFT) di soli 480 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

DeepSeek-V3-0324 · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 8K token (SWE-bench Verified 52.4% · GPQA Diamond 63.5%)
Throughput elevato di 65 token/secondo con latenza al primo token (TTFT) di soli 650 ms
Pesi aperti (671B (37B MoE)) 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 Vision 32B	DeepSeek-V3-0324
Cost per Task Estimated USD to finish one task	$0.22	$0.18
Output Tokens / Task Tokens generated per task	25K	45K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Aya Vision 32B	DeepSeek-V3-0324
Official API Model ID (SDK)	aya-vision-32b	deepseek-chat
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-03	2025-03
Knowledge Cutoff	January 2025	January 2025
Architecture	High-Capacity Multilingual VLM	671B Mixture-of-Experts (37B active)
Parameters	32B	671B (37B active MoE)
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 ($0.35/1M in) across full 16K window	Flat rate ($0.27/1M in) across full 128K window
Prompt Cache Policy & TTL	Cached input at $0.08/1M tokens	Automatic prefix caching at $0.07/1M (no extra cache-write fee)
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)	Text BPE (~4 chars/token)
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) · 416 GB VRAM (4-bit Quantized) · 1443 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	text
Output Modalities	text	text

Aya Vision 32B vs DeepSeek-V3-0324: Risposte Rapide (FAQ)

Which is more intelligent, Aya Vision 32B or DeepSeek-V3-0324?

DeepSeek-V3-0324 is more intelligent. It scores 48 compared with 45 on the composite Intelligence Index.

Which model is faster?

Aya Vision 32B is faster, generating 75 tokens per second compared with 65 tokens per second.

Which model has lower latency?

Aya Vision 32B has lower latency, with a time to first token of 0.48s compared with 0.65s.

Which model has a larger context window?

DeepSeek-V3-0324 has a larger context window, supporting 128K tokens compared with 16K tokens.

Verdetto

Sia Aya Vision 32B (Ideale per la traduzione multilingue ad alta precisione e la comunicazione aziendale globale, sistemi RAG aziendali e integrazioni API scalabili.) sia DeepSeek-V3-0324 (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: DeepSeek-V3-0324 guida nei benchmark di ragionamento e programmazione, Aya Vision 32B garantisce una generazione più rapida e Aya Vision 32B offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Aya Vision 32B o DeepSeek-V3-0324?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale DeepSeek-V3-0324. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Aya Vision 32B e DeepSeek-V3-0324?+

Aya Vision 32B costa $0.35 / $0.80 per milione di token di input/output, mentre DeepSeek-V3-0324 costa $0.27 / $1.10. Nel costo combinato, Aya Vision 32B risulta più economico.

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

Aya Vision 32B supporta 16K token di contesto contro 128K token di DeepSeek-V3-0324, mentre Aya Vision 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 Vision 32B vs DeepSeek-V3-0324

Cambia e Confronta Qualsiasi Modello

Aya Vision 32B

DeepSeek-V3-0324

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Aya Vision 32B · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek-V3-0324 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Aya Vision 32B vs DeepSeek-V3-0324: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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