Head-to-Head Model Comparison

Devstral Medium vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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Compare Devstral Medium by Mistral AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.

Confronto Diretto (VS)

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Popular Matchups:
Mistral AI

Devstral Medium

Modello di Ragionamento Profondo

Devstral Medium di Mistral AI è un modello di intelligenza artificiale con finestra di contesto da 128K token e tariffazione API di $0.8/1M token in input e $2.4/1M in output, ideale per coding, ragionamento e automazione aziendale.

Intelligence Index52 / 100
Input Token:

$0.80 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

51.5%

OpenAI

GPT-6 Astra

Modello di Ragionamento Profondo

GPT-6 Astra di OpenAI è un modello di intelligenza artificiale con finestra di contesto da 1M token e tariffazione API di $10.0/1M token in input e $50.0/1M in output, ideale per coding, ragionamento e automazione aziendale.

Intelligence Index96 / 100
Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Differenze Chiave a Colpo d’Occhio

  • Devstral Medium is 16.8x cheaper for API usage (input + output tokens combined).
  • GPT-6 Astra has a larger context window (272K vs 128K tokens).
  • GPT-6 Astra is faster at 100 tok/s vs 75 tok/s.
  • GPT-6 Astra leads on SWE-bench coding (82.4% vs 51.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureDevstral MediumGPT-6 Astra
Intelligence Index
Composite reasoning & knowledge score (0-100)
5296
Provider
Mistral AIOpenAI
Input Price
Cost per million input tokens
$0.80 / 1M$10.00 / 1M
Output Price
Cost per million output tokens
$2.40 / 1M$50.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.54 / 1M$7.70 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text272K tokens~408 A4 pages of text
Max Output Tokens
Per single request
33K128K
Throughput Speed
Tokens generated per second
75 tok/s100 tok/s
SWE-bench Verified
Real-world software engineering
51.5%82.4%
GPQA Diamond
Graduate-level reasoning
62%80.9%
Cached Input Price
Prompt caching discount per 1M tokens
$0.20 / 1M$1.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
GPT-6 Astra
+30.9% SWE-bench lead
Cost
Devstral Medium
16.8x cheaper monthly runtime
Speed
GPT-6 Astra
+33% faster generation
Context
GPT-6 Astra
272K tokens window

Punteggi Benchmark Verificati

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

Devstral MediumGPT-6 Astra
SWE-bench Verified (Autonomous Coding)

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

51.5%vs82.4%
GPQA Diamond (Doctorate-Level Science & Math)

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

62%vs80.9%
MMLU-Pro (Multi-task Language Understanding)

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

80.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1330ptsvs1520pts
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.

45%vs63.8%
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.

72%vs93.6%
Long-Context Reasoning

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

78%vs91.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

75 tok/s vs100 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
Devstral Medium0.50s
GPT-6 Astra0.95s
Est. End-to-End Response (500 tokens)TTFT + generation time
Devstral Medium7.17s
GPT-6 Astra5.95s

Simulatore Interattivo dei Costi Token

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)
Devstral Medium Monthly API Bill
$3.66 / month
$0.8/1M in · $2.4/1M out
GPT-6 Astra Monthly API Bill
$61.50 / month
$10/1M in · $50/1M out
Devstral Medium saves approximately $57.84 / month (94%) under this workload.16.8x Savings

Devstral Medium · Strengths & Key Advantages

  • Architettura High-Capacity Agentic Code Transformer avanzata di Mistral AI con supporto fino a 128K token di contesto
  • Ottimo rapporto qualità-prezzo ($0.8/1M input, $2.4/1M output) e bassa latenza
  • Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
  • L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
  • Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato

GPT-6 Astra · Strengths & Key Advantages

  • Architettura Omni-Adaptive Autoregressive with Dynamic CoT avanzata di OpenAI con supporto fino a 1M token di contesto
  • Ottimo rapporto qualità-prezzo ($10.0/1M input, $50.0/1M output) e bassa latenza
  • Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
  • L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
  • Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato

Token Use & Task Economics

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

MetricDevstral MediumGPT-6 Astra
Cost per Task
Estimated USD to finish one task
$0.55$2.15
Output Tokens / Task
Tokens generated per task
38K58K
Reasoning Tokens / Task
Thinking tokens burned per task
18K32K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureDevstral MediumGPT-6 Astra
Official API Model ID (SDK)devstral-medium-latestgpt-6-astra
API ProtocolMistral AI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-072026-09
Knowledge CutoffMay 2025June 2026
ArchitectureHigh-Capacity Agentic Code TransformerOmni-Adaptive Autoregressive with Dynamic CoT
ParametersConfidential (~70B)Confidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.8/1M in) across full 128K windowFlat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTLCached input at $0.2/1M 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 SupportAPI Prompt Engineering & RAG DistillationSupervised 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 VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationMistral AI Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio
Output Modalitiestexttext, audio

Devstral Medium vs GPT-6 Astra: Risposte Rapide (FAQ)

Which is more intelligent, Devstral Medium or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 52 on the composite Intelligence Index.

Which model is faster?

GPT-6 Astra is faster, generating 100 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Devstral Medium is cheaper at $0.54 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Devstral Medium has lower latency, with a time to first token of 0.50s compared with 0.95s.

Which model has a larger context window?

GPT-6 Astra has a larger context window, supporting 272K tokens compared with 128K tokens.

Verdetto

Choose Devstral Medium for automazione enterprise, sviluppo software, agenti ia autonomi e pipeline di produzione mistral ai, or choose GPT-6 Astra for automazione enterprise, sviluppo software, agenti ia autonomi e pipeline di produzione openai.

Domande Frequenti (FAQ)

Which is cheaper: Devstral Medium or GPT-6 Astra?+

Devstral Medium costs $0.8/1M input and $2.4/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.

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

Devstral Medium supports 128K 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.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fonti ufficiali: Mistral AI & OpenAI Official Documentation