Qwen Flash vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Qwen Flash by Alibaba against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Qwen Flash
Inferenza Ultra-RapidaQwen Flash di Alibaba è un modello di IA progettato per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, con finestra di contesto da 1M, velocità di 180 token/s, indice di intelligenza di 67/100 e tariffa di $
$0.02 / 1M
$0.08 / 1M
1M tokens
N/A
GPT-6 Astra
Modello Vocale e Audio NativoGPT-6 Astra di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 272K, velocità di 100 token/s, indice di intelligenza di 96/100 e tariffa
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Differenze Chiave a Colpo d’Occhio
- Qwen Flash is 585.7x cheaper for API usage (input + output tokens combined).
- Qwen Flash has a larger context window (1M vs 272K tokens).
- Qwen Flash is faster at 180 tok/s vs 100 tok/s.
| Feature | Qwen Flash | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 67 | 96 |
Provider | Alibaba | OpenAI |
Input Price Cost per million input tokens | $0.02 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $0.08 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.01 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 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 | 180 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.4% |
GPQA Diamond Graduate-level reasoning | N/A | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $1.00 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkEvaluations ongoing
Punteggi 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.
Qwen Flash · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 8K token (MMLU-Pro 63.5% · Arena Elo 1195)
- Throughput elevato di 180 token/secondo con latenza al primo token (TTFT) di soli 250 ms
- Economia API competitiva ($0.02/$0.08 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
GPT-6 Astra · Strengths & Key Advantages
- Finestra di contesto da 272K con capacità massima di output fino a 128K token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Throughput elevato di 100 token/secondo con latenza al primo token (TTFT) di soli 950 ms
- Economia API competitiva ($10/$50 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen Flash | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.01 | $2.15 |
Output Tokens / Task Tokens generated per task | 10K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 32K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen Flash | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | qwen-flash-instruct | gpt-6-astra |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-07 | 2026-09 |
| Knowledge Cutoff | May 2025 | June 2026 |
| Architecture | Ultra-Lightweight Distilled Autoregressive Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.02/1M in) across full 1000K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.002/1M 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 | API Prompt Engineering & RAG Distillation | 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 | Cloud-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 Classification | Alibaba Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 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 |
Qwen Flash vs GPT-6 Astra: Risposte Rapide (FAQ)
Which is more intelligent, Qwen Flash or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 67 on the composite Intelligence Index.
Which model is faster?
Qwen Flash is faster, generating 180 tokens per second compared with 100 tokens per second.
Which model is cheaper to run?
Qwen Flash is cheaper at $0.01 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen Flash has lower latency, with a time to first token of 0.25s compared with 0.95s.
Which model has a larger context window?
Qwen Flash has a larger context window, supporting 1M tokens compared with 272K tokens.
Verdetto
Choose Qwen Flash for ideale per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, sistemi rag aziendali e integrazioni api scalabili., or choose GPT-6 Astra for ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi rag aziendali e integrazioni api scalabili..
Domande Frequenti (FAQ)
Which is cheaper: Qwen Flash or GPT-6 Astra?+
Qwen Flash costs $0.02/1M input and $0.08/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Qwen Flash or GPT-6 Astra?+
Qwen Flash supports 1M 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: Alibaba & OpenAI Official Documentation