Codestral vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Codestral by Mistral AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Codestral
Modello a Pesi ApertiCodestral di Mistral AI è un modello di intelligenza artificiale con finestra di contesto da 256K token e tariffazione API di $0.2/1M token in input e $0.6/1M in output, ideale per coding, ragionamento e automazione aziendale.
$0.20 / 1M
$0.60 / 1M
256K tokens
28%
GPT-6 Astra
Modello di Ragionamento ProfondoGPT-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.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Differenze Chiave a Colpo d’Occhio
- 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%).
| Feature | Codestral | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 40 | 96 |
Provider | Mistral AI | OpenAI |
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 text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 8K | 128K |
Throughput Speed Tokens generated per second | 110 tok/s | 100 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 |
Chi vince in ogni categoria?
At-a-glance decision frameworkPunteggi Benchmark Verificati
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Codestral · Strengths & Key Advantages
- Architettura Code-Optimized Transformer with 32K Window avanzata di Mistral AI con supporto fino a 256K token di contesto
- Ottimo rapporto qualità-prezzo ($0.2/1M input, $0.6/1M 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.
| Metric | Codestral | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $2.15 |
Output Tokens / Task Tokens generated per task | 24K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 32K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Codestral | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | codestral-latest | gpt-6-astra |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-05 | 2026-09 |
| Knowledge Cutoff | May 2024 | June 2026 |
| Architecture | Code-Optimized Transformer with 32K Window | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | 22B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 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 window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) |
| 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) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-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 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision, audio |
| Output Modalities | text | text, audio |
Codestral vs GPT-6 Astra: Risposte Rapide (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.
Verdetto
Choose Codestral 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: 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.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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