Command A Plus vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Command A Plus by Cohere and GPT-6 Astra by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Command A Plus holds a notable pricing advantage for token ingestion. On output generation, Command A Plus is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, GPT-6 Astra provides an expanded memory horizon with 272K tokens. In latency-sensitive production environments, GPT-6 Astra leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
Changez et Comparez les Modèles
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Command A Plus
Command plus puissantde Cohere de référence 2026 multimodal phare moteur uniting visuel document raisonnement, profond chaîne de pensée, et souverain d'entreprise déploiement.
$3.00 / 1M
$12.00 / 1M
128K tokens
60.5%
GPT-6 Astra
Agent d'OS autonomed'OpenAI late-2026 phare modèle de fondation intégrant natif utilisation de l'ordinateur agents, dynamic UI orchestration, et profond STEM raisonnement.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Différences Clés en un Coup d’Œil
- Command A Plus is 3.7x 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 68 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 60.5%).
| Caractéristique | Command A Plus | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 96 |
Provider | Cohere | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $12.00 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.33 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 68 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 60.5% | 82.4% |
GPQA Diamond Graduate-level reasoning | 74% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.75 / 1M | $1.00 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
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.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Command A Plus · Strengths & Key Advantages
- de Cohere la plupart puissant modèle de fondation à date, blending vision, raisonnement, et agents
- Flawless récupération ancrage avec strict anti-hallucination citations vérification
- à poids ouverts availability pour souverain national et regulated d'entreprise déploiements
Considerations & Trade-offs
- Premium API token tarification ($3.00/$12.00)
- élevé matériel requirements pour local cluster auto-hébergement
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.
| Metric | Command A Plus | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $2.15 |
Output Tokens / Task Tokens generated per task | 45K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 32K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Command A Plus | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | command-a-plus | gpt-6-astra |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-05 | 2026-09 |
| Knowledge Cutoff | March 2026 | June 2026 |
| Architecture | Flagship Multimodal Agentic MoE | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential (~180B+ MoE) | 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 ($3/1M in) across full 128K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.75/1M 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) · Vision (~258–765 tokens per image tile) | 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) · 112 GB VRAM (4-bit Quantized) · 387 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, vision | text, vision, audio |
| Output Modalities | text | text, audio |
Command A Plus vs GPT-6 Astra: Réponses Rapides (FAQ)
Which is more intelligent, Command A Plus or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 58 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 68 tokens per second.
Which model is cheaper to run?
Command A Plus is cheaper at $2.33 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Command A Plus has lower latency, with a time to first token of 0.56s 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.
Verdict
Verdict & Model Selection Recommendation: Choose Command A Plus if your priority is Enterprise intelligence platforms, sovereign government automation, and mission-critical agent workflows. Its performance in demanding tasks justifies its operational token cost. Choose GPT-6 Astra if your workflow prioritizes Autonomous browser/computer workflows, real-time voice agents, and high-difficulty mathematical reasoning. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does Command A Plus compare to GPT-6 Astra in API token pricing and cost per token?+
Command A Plus costs $3.00 per 1M input tokens and $12.00 per 1M output tokens, whereas GPT-6 Astra costs $10.00 input and $50.00 output. Overall, Command A Plus is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Command A Plus or GPT-6 Astra?+
Command A Plus supports a context window of 128K tokens (~96k words), while GPT-6 Astra supports 272K tokens (~204k words). Therefore, GPT-6 Astra can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Command A Plus or GPT-6 Astra?+
Command A Plus scores 60.5% on SWE-bench Verified while GPT-6 Astra scores 82.4%. For autonomous software engineering and multi-file debugging, GPT-6 Astra holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Command A Plus and GPT-6 Astra?+
Command A Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-6 Astra provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Command A Plus and GPT-6 Astra?+
Command A Plus generates approximately 68 tokens per second, while GPT-6 Astra delivers 100 tokens per second. In latency-sensitive production environments, GPT-6 Astra provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Command A Plus and GPT-6 Astra to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Command A Plus to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-6 Astra. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs