Qwen: Qwen3 14B

Public pricingIntelligence 71/100Medium memoryगहरी सोचटूल उपयोग

Qwen: Qwen3 14B एक टेक्स्ट मॉडल है, जिसे तर्क और समस्या समाधान के लिए बनाया गया है। यह गहरी तर्कशक्ति और योजना، कम latency और efficient inference, 41K tokens का context और कम लागत profile जोड़कर reasoning, analysis, and hard problem solving में भरोसेमंद काम करता है। यह तब व्यावहारिक विकल्प है जब latency, cost और throughput महत्वपूर्ण हो, खासकर उन टीमों के लिए जिन्हें स्थिर output,

Input

$0.06/1M

Output

$0.24/1M

Cached

$0.02/1M

Batch

$0.04/1M

Calculate your Qwen3 14B bill.

Set your workload — see cost at your exact volume.

What would Qwen3 14B cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Qwen3 14B at a glance.

Memory

40,960

tokens

Max reply

40,960

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen3

Released

Apr 2025

Training cutoff

Jan 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • gpqa_diamond

    39.9

  • mmlu

    81

  • mmlu_pro

    61

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen3 14B

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Qwen3 14B — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen3 14B costs roughly $14 per month. Input is $0.06 /1M tokens and output is $0.24 /1M tokens.
Qwen3 14B has a 40,960-token context window (medium memory — a long report or a codebase file). That means you can fit about 7,680 words of input and history in a single call.
Beyond text generation, Qwen3 14B supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3 14B was released in April 2025, with training data cut off around January 2025.
Models in a similar class include Qwen3.5-Flash, Qwen3 8B, Qwen3 30B A3B. The "Similar models" section below this FAQ links into each.

Still unsure?

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