Head-to-Head Model Comparison

Aya Vision 32B vs DeepSeek-V3-0324

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

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

Model Multibahasa Global

Aya Vision 32B dari Cohere adalah model AI yang dirancang untuk penerjemahan multibahasa yang akurat dan komunikasi perusahaan global, menghadirkan jendela konteks 16K, kecepatan 75 token/detik, indeks kecerdasan 45/100, serta tarif $0.35/$

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

Model Dasar Bobot Terbuka

DeepSeek-V3-0324 dari DeepSeek adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 65 token/detik, indeks kecerdasan 48/100, serta tarif $

Intelligence Index48 / 100

Input Token:

$0.27 / 1M

Output Token:

$1.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

52.4%

Perbedaan Utama Sekilas

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

Siapa Unggul di Mana?

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

Skor Benchmark Terverifikasi

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

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

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

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)

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

Jendela konteks 16K dengan kapasitas output maksimum hingga 4K token (SWE-bench Verified 32% · GPQA Diamond 51.5%)
Kecepatan generasi tinggi 75 token/detik dengan latensi token pertama (TTFT) hanya 480 ms
Bobot terbuka (32B) 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

DeepSeek-V3-0324 · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 52.4% · GPQA Diamond 63.5%)
Kecepatan generasi tinggi 65 token/detik dengan latensi token pertama (TTFT) hanya 650 ms
Bobot terbuka (671B (37B MoE)) 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	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

Spesifikasi Teknis

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: Jawaban Cepat (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.

Kesimpulan

Baik Aya Vision 32B (Sangat cocok untuk penerjemahan multibahasa yang akurat dan komunikasi perusahaan global, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun DeepSeek-V3-0324 (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: DeepSeek-V3-0324 unggul dalam penalaran dan pemrograman, Aya Vision 32B memberikan kecepatan generasi token lebih tinggi, dan Aya Vision 32B lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Aya Vision 32B atau DeepSeek-V3-0324?+

Dalam indeks kecerdasan gabungan dan benchmark coding, DeepSeek-V3-0324 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Aya Vision 32B vs DeepSeek-V3-0324?+

Aya Vision 32B mengenakan biaya $0.35 / $0.80 per 1M token input/output, sedangkan DeepSeek-V3-0324 sebesar $0.27 / $1.10. Secara keseluruhan, Aya Vision 32B lebih hemat biaya.

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

Aya Vision 32B mendukung konteks 16K token dibandingkan 128K token pada DeepSeek-V3-0324, sementara Aya Vision 32B 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)

Aya Vision 32B vs DeepSeek-V3-0324

Ganti & Bandingkan Model Apa Saja

Aya Vision 32B

DeepSeek-V3-0324

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Aya Vision 32B · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek-V3-0324 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Aya Vision 32B vs DeepSeek-V3-0324: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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