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Model Comparison

DeepSeek V3.1 Terminus vs DeepSeek V4 Flash Vision ExpWhich Is Better in 2026?

DeepSeek: DeepSeek V3.1 Terminus logoDeepSeek•DeepSeek: DeepSeek V4 Flash Vision Exp logoDeepSeek

DeepSeek V3.1 Terminus vs DeepSeek V4 Flash Vision Exp: which should you choose in 2026?

DeepSeek V3.1 Terminus (by DeepSeek) and DeepSeek V4 Flash Vision Exp (by DeepSeek) 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.

At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison.

DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 163,840 tokens).

Choose DeepSeek V3.1 Terminus if…

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

Choose DeepSeek V4 Flash Vision Exp if…

  • • you work with longer documents, transcripts, or codebases
  • • you need image inputs

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.

Chat with both models
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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.

DeepSeek V3.1 Terminus and DeepSeek V4 Flash Vision Exp benchmark results
BenchmarkDeepSeek V3.1 TerminusDeepSeek V4 Flash Vision Exp
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

——
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

1415 ±10
—

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Aug 23, 2026.

Pricing, capabilities, and model facts

DeepSeek V3.1 Terminus and DeepSeek V4 Flash Vision Exp model facts
FeatureDeepSeek V3.1 TerminusDeepSeek V4 Flash Vision Exp
Context & model facts
DeveloperDeepSeekDeepSeek
API providerDeepSeekDeepSeek
Input context163,840 tokens1,048,576 tokens
Maximum output32,768 tokens384,000 tokens
Released——
Added to WritingmateSep 22, 2025Aug 21, 2026
LicenseNot availableNot available
Knowledge cutoff2025-03-31—
Capabilities
InputsTextText, Image
OutputsTextText
Provider endpoint accepts tool parametersYesYes
ReasoningYesYes
VisionNoYes
Image GenerationNoNo
Video GenerationNoNo
API pricing
Base input (per 1M tokens)$0.27$0.44
Base output (per 1M tokens)$1.00$1.32
Higher-context pricing tiersBase rate onlyBase rate only
Price-comparison caveatAt least one model changes token rates above a prompt-token threshold. Base rates are shown, but an unconditional blended price ratio would not be like-for-like.
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 21, 2026.

DeepSeek V3.1 Terminus vs DeepSeek V4 Flash Vision Exp FAQ

Which is better, DeepSeek V3.1 Terminus or DeepSeek V4 Flash Vision Exp?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison. DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 163,840 tokens).

Which model is cheaper to use through an API?

At least one model uses context-dependent token-pricing tiers, so the published base rates do not support an unconditional blended price comparison.

Which model supports more context?

DeepSeek V4 Flash Vision Exp has the larger context window (1,048,576 tokens vs 163,840 tokens).

Can I switch between DeepSeek V3.1 Terminus and DeepSeek V4 Flash Vision Exp?

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.