How much does Qwen3.6 27B cost?

Qwen3.6 27B costs $0.25/M input tokens and $2.00/M output tokens, with separate rates for Cache Read at $0.025/M tokens.

What is the context length of Qwen3.6 27B?

Qwen3.6 27B has a 262,144 token context window. It supports up to 65,536 completion tokens.

Does Qwen3.6 27B support tool calling and structured outputs?

Yes. Qwen3.6 27B accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Qwen3.6 27B support?

Qwen3.6 27B accepts text, images, and video as input and returns text.

Which providers serve Qwen3.6 27B?

Qwen3.6 27B is served by 6 providers on OpenRouter: Chutes, SiliconFlow, DeepInfra, Venice, Alibaba Cloud Int., and Reka AI. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was Qwen3.6 27B released?

Qwen3.6 27B was released on April 27, 2026.

Qwen: Qwen3.6 27B

qwen/qwen3.6-27b

Model weights

Compare

Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs — and supports a 262,144-token context window.

The model is designed for agentic coding and reasoning tasks, with particular strength in repository-level code comprehension, front-end development workflows, and multi-step problem solving. It includes a built-in thinking mode for extended reasoning and preserves thinking context across conversation history. Qwen3.6 27B supports 201 languages and dialects and is released under the Apache 2.0 license.

Modalities

In / out price

$0.25 / $2per 1M

Context

262K

Released

Apr 27, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


$0.32	$3.20	--	0.34s	63 tok/s	99.88%
$0.45	$2.70	--	0.86s	62 tok/s	99.69%
$0.325	$3.25	--	0.54s	71 tok/s	99.25%
$0.60	$6.00	$0.50	0.34s	60 tok/s	99.49%
$0.30	$3.20	--	2.76s	30 tok/s	93.60%
$0.25	$2.00	$0.025	5.52s	20 tok/s	98.45%

Input $0.32Output $3.20
63 tok/s99.88% uptime
Input $0.45Output $2.70
62 tok/s99.69% uptime
Input $0.325Output $3.25
71 tok/s99.25% uptime
Input $0.60Output $6.00
60 tok/s99.49% uptime
Input $0.30Output $3.20
30 tok/s93.60% uptime
Input $0.25Output $2.00
20 tok/s98.45% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.3218/M tokens

Output

$3.202/M tokens

Qwen3.6 27B — Price history

Price history

No effective price data for this selection

$0.177	$2.00	32.6%	12.1%
$0.300	$3.20	29.1%	2.5%
$0.320	$3.20	0.0%	66.1%
$0.325	$3.25	0.0%	5.4%
$0.450	$2.70	0.0%	9.5%
$0.543	$6.00	57.0%	4.3%

Effective in $0.177Effective out $2.00
Token share
12.1%
Effective in $0.300Effective out $3.20
Token share
2.5%
Effective in $0.320Effective out $3.20
Token share
66.1%
Effective in $0.325Effective out $3.25
Token share
5.4%
Effective in $0.450Effective out $2.70
Token share
9.5%
Effective in $0.543Effective out $6.00
Token share
4.3%

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

71tok/s

P50, best across providers

Latency

0.34s

P50, best provider

Latency / throughput

AutoExacto benchmarks

GPQA DiamondTAU-BenchChutes84.8%78.9%auto-routing85.1%78.1%Alibaba Cloud Int.84.2%76.7%SiliconFlow84.9%75.6%Venice85.7%74.3%

+2 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.28%

Availability over the last 3 days

Last 72 hours

Availability 99.28%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.22%

Without Routing

95.05%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Qwen: Qwen3.6 27B (Artificial Analysis and Vals AI)
Source	Benchmark	Score
Artificial Analysis	Qwen3.6 27B (Non-reasoning) Coding Index	46.6
Artificial Analysis	Qwen3.6 27B (Non-reasoning) GPQA Diamond	82.9%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) HLE	15.1%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) IFBench	45.7%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) τ²-Bench Telecom	93.6%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) AA-LCR	66.7%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) τ-Bench Banking	9.3%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) GDPval-AA	23.5%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) CritPt	0.9%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) Terminal-Bench Hard	21.2%
Artificial Analysis	Qwen3.6 27B (Non-reasoning) Terminal-Bench 2.1	51.3%
Artificial Analysis	Qwen3.6 27B (Reasoning) Coding Index	53.7
Artificial Analysis	Qwen3.6 27B (Reasoning) Agentic Index	18.5
Artificial Analysis	Qwen3.6 27B (Reasoning) GPQA Diamond	84.2%
Artificial Analysis	Qwen3.6 27B (Reasoning) HLE	23.1%
Artificial Analysis	Qwen3.6 27B (Reasoning) IFBench	67.6%
Artificial Analysis	Qwen3.6 27B (Reasoning) τ²-Bench Telecom	94.2%
Artificial Analysis	Qwen3.6 27B (Reasoning) AA-LCR	77.3%
Artificial Analysis	Qwen3.6 27B (Reasoning) τ-Bench Banking	16.7%
Artificial Analysis	Qwen3.6 27B (Reasoning) GDPval-AA	24.6%
Artificial Analysis	Qwen3.6 27B (Reasoning) CritPt	1.1%
Artificial Analysis	Qwen3.6 27B (Reasoning) SciCode	42.8%
Artificial Analysis	Qwen3.6 27B (Reasoning) Terminal-Bench Hard	34.8%
Artificial Analysis	Qwen3.6 27B (Reasoning) Terminal-Bench 4.0	0.0%
Artificial Analysis	Qwen3.6 27B (Reasoning) Terminal-Bench 2.1	60.7%
Vals AI	Qwen 3.6 27B CaseLaw v2	53.2%
Vals AI	Qwen 3.6 27B CorpFin v2	62.3%
Vals AI	Qwen 3.6 27B MortgageTax	68.3%
Vals AI	Qwen 3.6 27B ProofBench v1	8.0%
Vals AI	Qwen 3.6 27B SAGE v1	45.6%
Vals AI	Qwen 3.6 27B SWE-bench	70.0%
Vals AI	Qwen 3.6 27B TaxEval v2	71.3%
Vals AI	Qwen 3.6 27B Terminal-Bench 2.0	44.9%
Vals AI	Qwen 3.6 27B Vals Index	48.7%
Vals AI	Qwen 3.6 27B Vals Multimodal Index	50.2%
Vals AI	Qwen 3.6 27B Vibe Code Bench v1.1	11.9%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

1.32Btokens

Sparkfire

new

770Mtokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

579Mtokens

There are many coding agents, but this one is yours.

473Mtokens

qwen-rl-diffing

new

131Mtokens

Rest of OpenRouter

1.79B

Top 5 Apps

23.2M

Not currently available through EU in-region routing. In-region routing docs

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Qwen: Qwen3.6 27B

Providers