Head-to-Head Model Comparison

Qwen3 Coder Flash vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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Related topics (4)
AlibabaOpenAIlightweightflagship

Compare Qwen3 Coder Flash by Alibaba against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparação Direta (VS)

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Popular Matchups:
Alibaba

Qwen3 Coder Flash

IA de Alta Performance

O Qwen3 Coder Flash da Alibaba é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $0.1/1M na entrada e $0.4/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index77 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1M tokens

SWE-bench Verified:

N/A

OpenAI

GPT-6.1 Sol

Modelo de Raciocínio Profundo

O GPT-6.1 Sol da OpenAI é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $2.0/1M na entrada e $10.0/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Principais Diferenças em Resumo

  • Qwen3 Coder Flash is 23.1x cheaper for API usage (input + output tokens combined).
  • Qwen3 Coder Flash is faster at 130 tok/s vs 120 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3 Coder FlashGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
7794
Provider
AlibabaOpenAI
Input Price
Cost per million input tokens
$0.10 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.40 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.07 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
130 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
N/A82.3%
GPQA Diamond
Graduate-level reasoning
N/A80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.10 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Qwen3 Coder Flash
23.1x cheaper monthly runtime
Speed
Qwen3 Coder Flash
+8% faster generation
Context
Tied
1M tokens window

Pontuações de Benchmarks Verificadas

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

Qwen3 Coder FlashGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

N/Avs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

74.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1265ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs63.6%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

61.5%vs79.7%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs93.5%
Long-Context Reasoning

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

N/Avs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs120 tok/s

Latência e Tempo de Resposta

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
Qwen3 Coder Flash0.33s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3 Coder Flash4.18s
GPT-6.1 Sol5.29s

Simulador Interativo de Custo de Tokens

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)
Qwen3 Coder Flash Monthly API Bill
$0.53 / month
$0.1/1M in · $0.4/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Qwen3 Coder Flash saves approximately $11.63 / month (96%) under this workload.23.1x Savings

Qwen3 Coder Flash · Strengths & Key Advantages

  • Arquitetura Optimized Lightweight Hosted Code Transformer avançada da Alibaba com contexto de 1M tokens
  • Excelente relação custo-benefício ($0.1/1M entrada, $0.4/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

GPT-6.1 Sol · Strengths & Key Advantages

  • Arquitetura Near-Astra unified reasoning model avançada da OpenAI com contexto de 1M tokens
  • Excelente relação custo-benefício ($2.0/1M entrada, $10.0/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

Token Use & Task Economics

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

MetricQwen3 Coder FlashGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.03$2.05
Output Tokens / Task
Tokens generated per task
15K62K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3 Coder FlashGPT-6.1 Sol
Official API Model ID (SDK)qwen3-coder-flash-instructgpt-6-1-sol
API ProtocolAlibaba REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-072026-09
Knowledge CutoffMay 2025April 2026
ArchitectureOptimized Lightweight Hosted Code TransformerNear-Astra unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 1000K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.01/1M tokensAutomatic prefix caching at $0.1/1M (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)
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 ClassificationAlibaba 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
Output Modalitiestexttext

Qwen3 Coder Flash vs GPT-6.1 Sol: Respostas Rápidas (FAQ)

Which is more intelligent, Qwen3 Coder Flash or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 77 on the composite Intelligence Index.

Which model is faster?

Qwen3 Coder Flash is faster, generating 130 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Qwen3 Coder Flash is cheaper at $0.07 per 1M tokens blended, compared with $1.47 (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 1.12s.

Veredito

Choose Qwen3 Coder Flash for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com alibaba, or choose GPT-6.1 Sol for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com openai.

Perguntas Frequentes (FAQ)

Which is cheaper: Qwen3 Coder Flash or GPT-6.1 Sol?+

Qwen3 Coder Flash costs $0.1/1M input and $0.4/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Qwen3 Coder Flash or GPT-6.1 Sol?+

Qwen3 Coder Flash supports 1M tokens whereas GPT-6.1 Sol supports 1M 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.

Fontes oficiais: Alibaba & OpenAI Official Documentation