Tabbit
ResourcesBlogModels
Tabbit LogoTabbit

Tabbit — The AI Browser that Works for You

Topics

  • Best Browsers 2026: Rankings and Top Lists
  • AI Browser Guides and Resources
  • Browser Comparisons: Head-to-Head Guides
  • Browser Reviews and Explainers
  • Browser Alternatives
  • Browser Directory: Guides by Browser
  • Agentic Browser Resources
  • Browser Downloads and Install Guides
  • Browser Productivity Resources
  • SillyTavern Model Guides and Presets

Popular Guides

  • Best Browsers 2026: Top 10 Ranked & Compared
  • Best Free AI Browsers 2026: Plans & Prices Compared
  • Rabbit Browser: What It Is & Why Tabbit Is Better
  • Firefox vs Chrome 2026: Privacy, RAM & Speed Compared
  • Best Lightweight Browsers 2026: 7 Tested for RAM & Speed
  • AI Browser List 2026: 10 Browsers Compared
  • Neobrowser: Norton Neo, Download & Alternatives
  • Edge vs Chrome 2026: Speed, RAM & Battery Tested
  • Best Internet Browser for Android 2026
  • Best AI Browser 2026: Top 9 Tested & Ranked

Events

  • Tabbit Skill Competition
  • KPOP SBTI Fandom Personality Test
  • Tabbit Campus Creator Program
  • fifi's Picks: AI Skills for Research Papers
  • User Survey

About

  • Tabbit Blog
  • Press & Media
English
简体中文English
Reviews and evidence

DeepSeek V4.1 Flash · Community source · Personal experience

DeepSeek V4.1 Flash Roleplay: Diverging Experiences with Preset Adaptation and Runaway Long Replies

This discussion offers no single answer: CptPhantasmic found V4.1 Flash promising for writing style, instruction following, and detail handling in a short Janitor test, while MikabellStarfall encountered single replies exceeding **2,000 words**, loss of character control, and forgetting. Both emphasize the need to adjust the prompt or character card.

Unverified: the original source could not be rechecked. Historical figures below are not current verified results.

Community sourcePersonal experienceEdited 2026-09-20

Test conditions

Model/version
DeepSeek V4.1 Flash; exact snapshot follows the source
Source date
2026-09-10
Method/client
Source-specific benchmark, API, or client; see conditions
Review state
Dynamic source not reopened on 2026-09-20; values remain unverified

Key data and applicable tasks

One-sentence takeaway

This discussion offers no single answer: CptPhantasmic found V4.1 Flash promising for writing style, instruction following, and detail handling in a short Janitor test, while MikabellStarfall encountered single replies exceeding 2,000 words, loss of character control, and forgetting. Both emphasize the need to adjust the prompt or character card.

Use cases

  • Tasks it is suitable for assessing: Writing style, prompt adaptation, instruction following, character control, and plot continuity risks in Janitor roleplay.

  • Tasks it is unsuitable for extrapolating to: General model quality, a strict verdict on whether V4 Pro is better or worse, or consistent performance across all clients.

  • Applicable model version: DeepSeek V4.1 Flash.

  • Test environment or client: Both CptPhantasmic and MikabellStarfall mention Janitor; CptPhantasmic also says they plan to test a modified FF4 MAX+ prompt in SillyTavern (ST). The provider, full preset, and API configuration are not stated.

  • Reasoning tier and parameters: Not stated.

Evaluation method

The main post only asks whether V4.1 Flash is better than V4 Pro; it defines no task set. CptPhantasmic says they ran a quick test on a small number of bots in Janitor, while MikabellStarfall describes an experience using a starter prompt. Comments also suggest adjusting the preset, prompt, and character card for each model. There was no uniform prompt, sample size, number of repetitions, baseline, or independent review, so this can only be treated as community opinion.

Key results

  • Positive experience: CptPhantasmic says that after tweaking the prompt, the model performed “quite well.” Its writing style differs from Pro-0813, it can adapt to different types, and it follows instructions and details relatively well. He says it did not skip or skim prompts and replies as V4 Flash did, and he did not encounter common DeepSeek stock phrasing. This conclusion comes from a small, quick Janitor test and does not cover deep plotlines or positivity bias.

  • Negative experience: MikabellStarfall says Janitor turns the opening prompt into a short story of 2,000+ words, follows the opening only loosely, and adds setting, character details, and plot. Even when the prompt says not to take over the user's turn, it takes over the entire scene, making back-and-forth co-writing difficult. She also describes the model as very forgetful: the prompt specified the Grand Pas de Deux from The Nutcracker, but the model wrote the Sugar Plum Fairy instead, and in the same message regressed to Act I.

  • Other signals: Kahvana says the preset and character card should be adjusted for the new model; PhysicalKnowledge also says the prompt needs slight changes. ForwardMastodon considers it worse than V4 Flash; SleepBaobei reports frequent logical errors and hallucinations in simple plots. These opinions conflict and cannot be combined into a single score.

Raw data

ObserverClient and scopeObserved phenomenon
CptPhantasmicJanitor; quick test on a small number of botsDifferent writing style, adaptation to different types, and relatively good instruction and detail following; prompt still needs fine-tuning
MikabellStarfallJanitor; a single starter prompt2,000+ words, extra details, taking over the scene, and continuity and memory problems
Kahvana, PhysicalKnowledgeClient not fully specifiedSuggested adjusting the preset, character card, or prompt
Thread snapshot5 upvotes, 16 commentsDiscussion size, not an evaluation score

Conclusions and limitations

This post supports a narrow conclusion: the roleplay experience with V4.1 Flash may depend heavily on Janitor's preset, character card, and prompt design. It may improve writing style and instruction following, or it may disrupt co-writing through overgeneration. MikabellStarfall's The Nutcracker mix-up is a single continuity case and is insufficient to prove a general memory defect; CptPhantasmic's positive conclusion also covers only a short test. The original post does not disclose the full preset or prompt, so it cannot support a claim that a directly copyable configuration exists.

Reproduction notes

Fix the same Janitor character card, preset, opening prompt, temperature, and other parameters, then run V4.1 Flash alongside a comparison model with an explicit version. Repeat the test while recording reply word count, extra facts, whether the model takes over the user's character, instruction following, and cross-turn plot consistency. If using the modified FF4 MAX+ prompt in ST, obtain the complete text and record the configuration; the post itself does not provide them, so it cannot be directly reproduced from this material.

What this supports

  • This discussion offers no single answer: CptPhantasmic found V4.1 Flash promising for writing style, instruction following, and detail handling in a short Janitor test, while MikabellStarfall encountered single replies exceeding **2,000 words**, loss of character control, and forgetting. Both emphasize the need to adjust the prompt or character card.

What this does not support

  • Does not yield one role-play verdict because character cards, prompts, length settings, and samples differ; it only supports a tuning recommendation.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

Reddit, r/SillyTavernAI · Quirky-Opinion3286 (main post); CptPhantasmic, MikabellStarfall, Kahvana, PhysicalKnowledge, ForwardMastodon, SleepBaobei (comments) · Original publication date 2026-09-10 · Site edit date 2026-09-20

Open original source

DeepSeek V4.1 Flash

Compare DeepSeek V4.1 Flash in Tabbit

Download the Tabbit client to check model access

Read the full analysis

Overview · English

DeepSeek V4.1 Flash: the exact model, new architecture, and where the low price fits

DeepSeek V4.1 Flash is the current deepseek-flash route with 1M context, native vision and scheduled pricing—but old V4 Flash and V4 Pro evidence must stay separate.

Related reviews

DeepSeek V4.1 Flash Generates a Browser Tactical Shooter in OpenCode in a Single Run: A Field Report on the Artifact and CostTarun122 says they used a large prompt in OpenCode to have DeepSeek V4.1 Flash generate a playable browser tactical shooter in about ten minutes, at a total cost of approximately $0.28 and roughly 300k tokens; the public demo page and code repository support the claim that the artifact exists, but the original post provides no complete prompt, configuration, execution logs, or baseline. This is therefore a personal field report with a public result, rather than a controlled evaluation.DeepSeek-V4.1-Flash (Max): Task Cost and Net Improvement in Agent ArenaArena.ai reports a **+4.87%** net improvement for DeepSeek-V4.1-Flash (Max) relative to the Arena baseline. The body of the post states a **$0.07** median cost per task, while the detailed table states **$0.06**. The cost should therefore be recorded as an inconsistency in the original post, rather than combined into one unconditionally certain figure.Artificial Analysis: DeepSeek V4.1 Flash's Intelligence, Cost, and Hallucination BoundariesAt the `Reasoning, Max Effort` setting, Artificial Analysis gives DeepSeek V4.1 Flash an Artificial Analysis Intelligence Index score of about 40. It is attractive for agent tasks, long-context work, and cost, but its outputs are extremely verbose, and its AA-Omniscience Non-Hallucination Rate is only 4%, so “cheap” cannot be equated directly with reliable.DeepSeek-V4.1-Flash Official Model Card Benchmarks: Agent Strengths and Harness BoundariesThe official model card shows that DeepSeek-V4.1-Flash is a multimodal MoE with a 552B backbone and 8B (prefill) / 16B (decode) activated per token; with the specified maximum reasoning effort and Agent harness, it scores 90.6 on Terminal-Bench 2.1 and 74.2 on DeepSWE v1.1, both above DeepSeek-V4-Flash in the table. Those numbers demonstrate the combined performance of the “model + harness + parameters” configuration and cannot be generalized as uniform capability across all clients or ordinary conversational tasks.DeepSeek-V4.1-Flash: Breaking Down Ice Cream App Requirements with a Markdown Specification DocumentFirst have the model turn the requirements into one or more Markdown specification documents, then use those documents to drive implementation; the prompt asks the model to cover target customers, regions, parameters, technical scope, andFirst-call API configurationUse deepseek-flash as the model name for the first call; the old aliases are still accepted, but requests are served by DeepSeek-V4.1-Flash and billed at Flash pricing. The official example uses an OpenAI-compatible format, thinking enablThinking-mode parameter selectionThe current API uses deepseek-flash to access DeepSeek-V4.1-Flash; thinking mode is enabled by default with a default effort of high, request tiers map to low, high, or max according to the official mapping, and multi-turn requests with tQuestion-and-answer JSON extractionAn English systemprompt that includes an example can make the DeepSeek API extract question-and-answer text into JSON; the call must also set responseformat to {'type': 'jsonobject'}. The official documentation also notes that the prompt