Qwen3 Coder Flash vs Qwen3-Coder 480B-A35B Instruct
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Qwen3 Coder Flash di Alibaba e Qwen3-Coder 480B-A35B Instruct di Alibaba sono due modelli di IA di riferimento. Qwen3 Coder Flash offre una finestra di contesto di 1M token a $0.10/$0.40 per milione di token, mentre Qwen3-Coder 480B-A35B Instruct mette a disposizione 262.1K token di contesto a $0.00/$0.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.
Cambia e Confronta Qualsiasi Modello
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Qwen3 Coder Flash
Inferenza Ultra-RapidaQwen3 Coder 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 130 token/s, indice di intelligenza di 77/100 e tarif
$0.10 / 1M
$0.40 / 1M
1M tokens
N/A
Qwen3-Coder 480B-A35B Instruct
Modello Base a Pesi ApertiQwen3-Coder 480B-A35B Instruct di Alibaba è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 262K, velocità di 52 token/s, indice di intelli
$0.00 / 1M
$0.00 / 1M
262.1K tokens
56.5%
Differenze Chiave a Colpo d’Occhio
- Qwen3-Coder 480B-A35B Instruct is 1.0x cheaper for API usage (input + output tokens combined).
- Qwen3 Coder Flash has a larger context window (1M vs 262K tokens).
- Qwen3 Coder Flash is faster at 130 tok/s vs 52 tok/s.
| Feature | Qwen3 Coder Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 77 | 86 |
Provider | Alibaba | Alibaba |
Input Price Cost per million input tokens | $0.10 / 1M | $0.00 / 1M |
Output Price Cost per million output tokens | $0.40 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.07 / 1M | $0.00 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 130 tok/s | 52 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 56.5% |
GPQA Diamond Graduate-level reasoning | N/A | 70% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $0.00 / 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.
Contamination-free competitive programming problems collected continuously over time.
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.
Qwen3 Coder Flash · Strengths & Key Advantages
- Finestra di contesto da 1M con capacità massima di output fino a 8K token (MMLU-Pro 74.5% · Arena Elo 1265)
- Throughput elevato di 130 token/secondo con latenza al primo token (TTFT) di soli 330 ms
- Economia API competitiva ($0.1/$0.4 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
Qwen3-Coder 480B-A35B Instruct · Strengths & Key Advantages
- Finestra di contesto da 262K con capacità massima di output fino a 16K token (SWE-bench Verified 56.5% · GPQA Diamond 70%)
- Throughput elevato di 52 token/secondo con latenza al primo token (TTFT) di soli 760 ms
- Pesi aperti (480B total (35B MoE)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
- Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3 Coder Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.03 | $0.00 |
Output Tokens / Task Tokens generated per task | 15K | 25K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 9K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen3 Coder Flash | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Official API Model ID (SDK) | qwen3-coder-flash-instruct | qwen3-coder-480b-a35b-instruct |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-07 | 2025-04 |
| Knowledge Cutoff | May 2025 | March 2025 |
| Architecture | Optimized Lightweight Hosted Code Transformer | Code-Specialized Sparse Mixture-of-Experts Transformer |
| Parameters | Confidential | 480B total (35B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.1/1M in) across full 1000K window | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | Cached input at $0.01/1M tokens | Automatic prefix KV-caching in vLLM / SGLang (0 cost) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 298 GB VRAM (4-bit Quantized) · 1032 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Alibaba Production Safety & Alignment Verified | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text |
| Output Modalities | text | text |
Qwen3 Coder Flash vs Qwen3-Coder 480B-A35B Instruct: Risposte Rapide (FAQ)
Which is more intelligent, Qwen3 Coder Flash or Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is more intelligent. It scores 86 compared with 77 on the composite Intelligence Index.
Which model is faster?
Qwen3 Coder Flash is faster, generating 130 tokens per second compared with 52 tokens per second.
Which model is cheaper to run?
Qwen3-Coder 480B-A35B Instruct is cheaper at $0.00 per 1M tokens blended, compared with $0.07 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3 Coder Flash has lower latency, with a time to first token of 0.33s compared with 0.76s.
Which model has a larger context window?
Qwen3 Coder Flash has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Verdetto
Sia Qwen3 Coder Flash (Ideale per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, sistemi RAG aziendali e integrazioni API scalabili.) sia Qwen3-Coder 480B-A35B Instruct (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Qwen3-Coder 480B-A35B Instruct guida nei benchmark di ragionamento e programmazione, Qwen3 Coder Flash garantisce una generazione più rapida e Qwen3-Coder 480B-A35B Instruct offre il miglior rapporto qualità-prezzo per carichi API elevati.
Domande Frequenti (FAQ)
Quale modello è migliore per coding e ragionamento, Qwen3 Coder Flash o Qwen3-Coder 480B-A35B Instruct?+
Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Qwen3-Coder 480B-A35B Instruct. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.
Qual è la differenza di prezzo API tra Qwen3 Coder Flash e Qwen3-Coder 480B-A35B Instruct?+
Qwen3 Coder Flash costa $0.10 / $0.40 per milione di token di input/output, mentre Qwen3-Coder 480B-A35B Instruct costa $0.00 / $0.00. Nel costo combinato, Qwen3-Coder 480B-A35B Instruct risulta più economico.
Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+
Qwen3 Coder Flash supporta 1M token di contesto contro 262.1K token di Qwen3-Coder 480B-A35B Instruct, mentre Qwen3 Coder Flash offre una velocità di generazione superiore.
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: Documentazione API ufficiale di Alibaba e Alibaba, schede di sistema e benchmark indipendenti (2026).