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Model Comparison

Qwen3.8 27B vs GLM 5V TurboWhich Is Better in 2026?

Qwen: Qwen3.8 27B logoQwen•
Z.AI

Qwen3.8 27B vs GLM 5V Turbo: which should you choose in 2026?

Qwen3.8 27B (by Qwen) and GLM 5V Turbo (by Z.AI) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Qwen3.8 27B is about 1.7× cheaper on a blended 3:1 input/output basis ($1.14 vs $1.90 per 1M tokens).

Qwen3.8 27B has the larger context window (1,000,000 tokens vs 202,752 tokens).

Choose Qwen3.8 27B if…

  • • lower blended API cost matters for your workload
  • • you work with longer documents, transcripts, or codebases

Choose GLM 5V Turbo if…

  • • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

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Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Qwen3.8 27B and GLM 5V Turbo benchmark results
BenchmarkQwen3.8 27BGLM 5V Turbo
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

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BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

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OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

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SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

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Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

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AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

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GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

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Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

——
Arena preference scores
Arena (Text)

Human preference score

—
1433 ±7
Arena (Code/WebDev)

Human preference score for code and web development

—
1400 ±14

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Aug 22, 2026.

Pricing, capabilities, and model facts

Qwen3.8 27B and GLM 5V Turbo model facts
FeatureQwen3.8 27BGLM 5V Turbo
Context & model facts
DeveloperQwenZ.AI
API providerQwenZ.ai
Input context1,000,000 tokens202,752 tokens
Maximum output131,072 tokens131,072 tokens
Released——
Added to WritingmateAug 14, 2026Apr 1, 2026
LicenseNot availableNot available
Knowledge cutoff——
Capabilities
InputsText, Image, VideoImage, Text, Video
OutputsTextText
Provider endpoint accepts tool parametersYesYes
ReasoningYesYes
VisionYesYes
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.45$1.20
Output (per 1M tokens)$3.20$4.00
Blended 3:1 input/output$1.14$1.90
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Aug 14, 2026.

Why Pay for Multiple Subscriptions?

Comparing Qwen3.8 27B from Qwen with GLM 5V Turbo from Z.AI? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Qwen3.8 27B and GLM 5V Turbo
PlanPriceQwen3.8 27BGLM 5V TurboAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
View Plans & Pricing

Qwen3.8 27B vs GLM 5V Turbo FAQ

Which is better, Qwen3.8 27B or GLM 5V Turbo?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Qwen3.8 27B is about 1.7× cheaper on a blended 3:1 input/output basis ($1.14 vs $1.90 per 1M tokens). Qwen3.8 27B has the larger context window (1,000,000 tokens vs 202,752 tokens).

Which model is cheaper to use through an API?

Qwen3.8 27B is about 1.7× cheaper on a blended 3:1 input/output basis ($1.14 vs $1.90 per 1M tokens).

Which model supports more context?

Qwen3.8 27B has the larger context window (1,000,000 tokens vs 202,752 tokens).

Can I switch between Qwen3.8 27B and GLM 5V Turbo?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.