Head-to-Head Model Comparison

Codestral vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
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Mistral AIOpenAIcodingflagship

Compare Codestral by Mistral AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparaison Face-à-Face (VS)

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Popular Matchups:
Mistral AI

Codestral

Titan du code européen

de Mistral dédié code moteur trained à travers 80+ programmation langues, intégrant fill-dans-le-middle et 32K contexte tailored pour développeur productivity.

Intelligence Index40 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

256K tokens

SWE-bench Verified:

28%

OpenAI

GPT-6 Astra

Agent d'OS autonome

d'OpenAI late-2026 phare modèle de fondation intégrant natif utilisation de l'ordinateur agents, dynamic UI orchestration, et profond STEM raisonnement.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Différences Clés en un Coup d’Œil

  • Codestral is 67.2x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 256K tokens).
  • Codestral is faster at 110 tok/s vs 100 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 28.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaractéristiqueCodestralGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
4096
Provider
Mistral AIOpenAI
Input Price
Cost per million input tokens
$0.20 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$0.60 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.14 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
110 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
28%82.4%
GPQA Diamond
Graduate-level reasoning
42%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.05 / 1M$1.00 / 1M

Qui gagne où ?

At-a-glance decision framework
Code
GPT-6 Astra
+54.4% SWE-bench lead
Coût
Codestral
67.2x cheaper monthly runtime
Vitesse
Codestral
+10% faster generation
Contexte
GPT-6 Astra
272K tokens window

Scores de Benchmarks Vérifiés

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

CodestralGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

28%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

42%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

70%vs89.9%
LMSYS Chatbot Arena Elo

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

1240ptsvs1520pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs63.8%
SciCode (Scientific Computing)

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

N/Avs54.9%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.8%
AIME (Advanced Math Competition)

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

N/Avs93.6%
Long-Context Reasoning

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

N/Avs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs100 tok/s

Latence et Temps de Réponse

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
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Codestral4.90s
GPT-6 Astra5.95s

Simulateur Interactif de Coût de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Codestral Monthly API Bill
$0.92 / month
$0.2/1M in · $0.6/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Codestral saves approximately $60.59 / month (99%) under this workload.67.2x Savings

Codestral · Strengths & Key Advantages

  • Fluent dans sur 80 programmation langues de Python et TypeScript à Rust et COBOL
  • Fill-dans-le-Middle (FIM) optimisation tailored pour en temps réel IDE code completion
  • rapide inférence (110 tok/s) à économique-friendly développeur tarification
Considerations & Trade-offs
  • Non-production license pour direct weight downloads (Mistral Non-production License)
  • 32K fenêtre de contexte peut be tight pour immense multi-service mono-repos

GPT-6 Astra · Strengths & Key Advantages

  • Flawless OS-level navigation et utilisation de l'ordinateur automatisation
  • Seamless en temps réel multimodal voix et vision interactivity
  • Dynamic chaîne de pensée qui self-adjusts profondeur based sur query difficulty
  • immense 1M fenêtre de contexte avec instant prefix caching
Considerations & Trade-offs
  • Strict sécurité filters peut occasionally throttle complexe penetration testing prompts
  • Slightly supérieur raisonnement latence sur élevé-effort mathématiques queries

Token Use & Task Economics

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

MetricCodestralGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.20$2.15
Output Tokens / Task
Tokens generated per task
24K58K
Reasoning Tokens / Task
Thinking tokens burned per task
0K32K

Spécifications Techniques

Architecture, release timeline, capabilities, and modalities.

CaractéristiqueCodestralGPT-6 Astra
Official API Model ID (SDK)codestral-latestgpt-6-astra
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI Responses API & Chat Completions v1
Release Date2024-052026-09
Knowledge CutoffMay 2024June 2026
ArchitectureCode-Optimized Transformer with 32K WindowOmni-Adaptive Autoregressive with Dynamic CoT
Parameters22BConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.2/1M in) across full 256K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.05/1M tokensAutomatic prefix caching at $1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 14 GB VRAM (4-bit Quantized) · 47 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

Codestral vs GPT-6 Astra: Réponses Rapides (FAQ)

Which is more intelligent, Codestral or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 40 on the composite Intelligence Index.

Which model is faster?

Codestral is faster, generating 110 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

Codestral is cheaper at $0.14 per 1M tokens blended, compared with $7.70 (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 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 256K tokens.

Verdict

Choose Codestral for vs code et jetbrains extension backends, automatisé test génération, et multi-langue traduction, or choose GPT-6 Astra for autonome browser/computer flux de travail, en temps réel voix agents, et élevé-difficulty mathématique raisonnement.

Questions fréquentes

Which is cheaper: Codestral or GPT-6 Astra?+

Codestral costs $0.2/1M input and $0.6/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

Which model has a larger context window: Codestral or GPT-6 Astra?+

Codestral supports 256K tokens whereas GPT-6 Astra supports 272K tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: Mistral AI & OpenAI Official Documentation