Head-to-Head Model Comparison

Codestral vs DeepSeek-Coder-V2 236B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

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CodestralProfile

DeepSeek-Coder-V2 236BProfile

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Mistral AI

Codestral

Açık Ağırlıklı Kodlama Uzmanı

Mistral AI tarafından geliştirilen Codestral; kendi sunucunuzda barındırılabilir açık ağırlıklı yazılım geliştirme ve kod üretimi için tasarlanmış olup 256K bağlam penceresi, 110 token/sn hız, 40/100 zeka indeksi ve 1M token başına $0.2/$0.

Intelligence Index40 / 100

Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

28%

DeepSeek

DeepSeek-Coder-V2 236B

Açık Ağırlıklı Temel Model

DeepSeek tarafından geliştirilen DeepSeek-Coder-V2 236B; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 128K bağlam penceresi, 74 token/sn hız, 42/100 zeka indeksi ve 1M token b

Intelligence Index42 / 100

Input Token:

$0.14 / 1M

Output Token:

$0.28 / 1M

Context Window:

128K tokens

SWE-bench Verified:

42.1%

Bir Bakışta Temel Farklar

DeepSeek-Coder-V2 236B is 1.9x cheaper for API usage (input + output tokens combined).
Codestral has a larger context window (256K vs 128K tokens).
Codestral is faster at 110 tok/s vs 74 tok/s.
DeepSeek-Coder-V2 236B leads on SWE-bench coding (42.1% vs 28.0%).

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

Feature	Codestral	DeepSeek-Coder-V2 236B
Intelligence Index Composite reasoning & knowledge score (0-100)	40	42
Provider	Mistral AI	DeepSeek
Input Price Cost per million input tokens	$0.20 / 1M	$0.14 / 1M
Output Price Cost per million output tokens	$0.60 / 1M	$0.28 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.14 / 1M	$0.07 / 1M
Context Window Maximum input + output tokens	256K tokens~384 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	110 tok/s	74 tok/s
SWE-bench Verified Real-world software engineering	28%	42.1%
GPQA Diamond Graduate-level reasoning	42%	49.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.05 / 1M	$0.01 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

DeepSeek-Coder-V2 236B

+14.1% SWE-bench lead

Cost

DeepSeek-Coder-V2 236B

1.9x cheaper monthly runtime

Speed

Codestral

+49% faster generation

Context

Codestral

256K tokens window

Doğrulanmış Benchmark Puanları

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

CodestralDeepSeek-Coder-V2 236B

SWE-bench Verified (Autonomous Coding)

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

28%vs42.1%

GPQA Diamond (Doctorate-Level Science & Math)

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

42%vs49.5%

MMLU-Pro (Multi-task Language Understanding)

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

70%vs69.8%

LMSYS Chatbot Arena Elo

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

1240ptsvs1272pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs5.8%

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs27.8%

SciCode (Scientific Computing)

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

N/Avs29.4%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs48.6%

AIME (Advanced Math Competition)

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

N/Avs61.2%

Long-Context Reasoning

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

N/Avs66.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs74 tok/s

Gecikme Süresi ve Yanıt Hızı

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

Codestral0.35s

DeepSeek-Coder-V2 236B0.51s

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

Codestral4.90s

DeepSeek-Coder-V2 236B7.27s

Gerçek Zamanlı Token Maliyet Simülatörü

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)

Codestral Monthly API Bill

$0.92 / month

$0.2/1M in · $0.6/1M out

DeepSeek-Coder-V2 236B Monthly API Bill

$0.48 / month

$0.14/1M in · $0.28/1M out

DeepSeek-Coder-V2 236B saves approximately $0.43 / month (47%) under this workload.1.9x Savings

Codestral · Strengths & Key Advantages

256K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 28% · GPQA Diamond 42%)
Sadece 350 ms ilk token gecikmesi (TTFT) ile saniyede 110 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (22B)

Considerations & Trade-offs

Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

DeepSeek-Coder-V2 236B · Strengths & Key Advantages

128K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 42.1% · GPQA Diamond 49.5%)
Sadece 510 ms ilk token gecikmesi (TTFT) ile saniyede 74 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (236B)

Considerations & Trade-offs

Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Token Use & Task Economics

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

Metric	Codestral	DeepSeek-Coder-V2 236B
Cost per Task Estimated USD to finish one task	$0.20	$0.14
Output Tokens / Task Tokens generated per task	24K	30K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Codestral	DeepSeek-Coder-V2 236B
Official API Model ID (SDK)	codestral-latest	deepseek-chat
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2024-05	2024-06
Knowledge Cutoff	May 2024	December 2023
Architecture	Code-Optimized Transformer with 32K Window	236B Mixture-of-Experts (21B active)
Parameters	22B	236B
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 ($0.2/1M in) across full 256K window	Flat rate ($0.14/1M in) across full 128K window
Prompt Cache Policy & TTL	Cached input at $0.05/1M tokens	Automatic prefix caching at $0.014/1M (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)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 14 GB VRAM (4-bit Quantized) · 47 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 146 GB VRAM (4-bit Quantized) · 507 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
Output Modalities	text	text

Codestral vs DeepSeek-Coder-V2 236B: Hızlı Yanıtlar (SSS)

Which is more intelligent, Codestral or DeepSeek-Coder-V2 236B?

DeepSeek-Coder-V2 236B is more intelligent. It scores 42 compared with 40 on the composite Intelligence Index.

Which model is faster?

Codestral is faster, generating 110 tokens per second compared with 74 tokens per second.

Which model is cheaper to run?

DeepSeek-Coder-V2 236B is cheaper at $0.07 per 1M tokens blended, compared with $0.14 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Codestral has lower latency, with a time to first token of 0.35s compared with 0.51s.

Which model has a larger context window?

Codestral has a larger context window, supporting 256K tokens compared with 128K tokens.

Sonuç

Hem Codestral (kendi sunucunuzda barındırılabilir açık ağırlıklı yazılım geliştirme ve kod üretimi, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de DeepSeek-Coder-V2 236B (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: DeepSeek-Coder-V2 236B karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Codestral daha yüksek üretim hızı sağlar; DeepSeek-Coder-V2 236B ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Codestral mi yoksa DeepSeek-Coder-V2 236B mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde DeepSeek-Coder-V2 236B önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Codestral ve DeepSeek-Coder-V2 236B API fiyatları nasıl karşılaştırılır?+

Codestral 1M giriş/çıkış tokeni başına $0.20 / $0.60 ücretlendirilirken, DeepSeek-Coder-V2 236B $0.14 / $0.28 seviyesindedir. Karma maliyette DeepSeek-Coder-V2 236B daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Codestral 256K token bağlam penceresi sunarken DeepSeek-Coder-V2 236B 128K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Codestral öndedir.

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)

Codestral vs DeepSeek-Coder-V2 236B

İstediğiniz Modelleri Seçin ve Karşılaştırın

Codestral

DeepSeek-Coder-V2 236B

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Codestral · Strengths & Key Advantages

Considerations & Trade-offs

DeepSeek-Coder-V2 236B · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Codestral vs DeepSeek-Coder-V2 236B: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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