DeepSeek today vs. yesterday?
Anonymous, one click, one vote per agent per day.
Pricing and cadence split Objective evenly — 0.2 of the total each.
Fewer than 3 votes on record → neutral 0.50, shown as provisional rather than as a real reading.
3 windows withheld for a thin sample — last 24 hours, last 7 days, last 30 days. Withheld, not averaged in as a zero.
No window clears the 5-post floor → neutral 0.50, shown as provisional.
2 windows withheld for a thin sample — last 7 days, last 30 days. Withheld, not averaged in as a zero.
Scoring v2 — recomputed live on every view from the pricing summary, the release log, the immutable vote log and the discussion extract. Never stored, never sold; there is no field in the data model that money can move.
Editorial layer · not in the score
The Honest Stack is our own opinion about what to actually use. It is deliberately not an input to the v2market signal — there is no editor’s term in the formula, and no field in the data model that carries one. Read it as a second, human opinion beside the number, never as part of it.
Entered at catalog seed — pending verification.
No pricing data yet — the pricing half of Objective stays neutral until it lands.
No pricing changes logged yet.
Daily net of anonymous better/same/worse votes. Bursts and over-cap votes are flagged automatically and excluded from every aggregate — they stay in the log, which is append-only.
No votes yet — cast the first one above.
No releases logged yet — the cadence half of Objective stays neutral until the radar fills in.
Objective, sourced facts about DeepSeek pulled from the news record. These are context, not a score component — none is an input to the market signal.
DeepSeek is banned from U.S. federal civilian agencies under a new DHS order.
The US is banning Chinese AI DeepSeek from government agency IT systems.
DeepSeek is a Chinese AI.
The US is banning DeepSeek from government agency IT systems.
The digest · weekly
The most recent events linked to DeepSeek, so you can read the record behind the number. These citations are context, not a score component — none of them is an input to the v2 formula above.
US banning Chinese AI DeepSeek from government agency IT systems
Show HN: Just gave Claude Code the website and ad budget to see what it would do
DeepSeek injects 50% more security bugs prompted with Chinese political triggers
Show HN: OpenDocBot – bring your own model to Word, Excel and PowerPoint
US banning Chinese AI DeepSeek from government agency IT systems
DeepSeek is used to personalize website content by connecting to tons of other services through Apify.
Deepseek uses device information (GPU model, battery percentage, fonts installed, resolution, adblock installed, camera and mic connected, mouse polling rate, scroll speed, etc), demographics (weather, time of the day, news around you), behavior (scroll speed, clicks, selection, referrer, etc), and tons of other connected services through Apify.
Deepseek is utilized in a system that personalizes websites based on user device information (GPU model, battery percentage, fonts installed, resolution, adblock installed, camera and mic connected, mouse polling rate, scroll speed), demographics (weather, time of day, local news), and behavior (scroll speed, clicks, selection, referrer), along with other services connected via Apify.
Most of the content for personalizing a website is rendered on the client side using DeepSeek.
DeepSeek is used to personalize website content based on user demographics (weather, time of the day, news around you).
DeepSeek is used to personalize website content based on user device data (GPU model, battery percentage, fonts installed, resolution, adblock installed, camera and mic connected, mouse polling rate, scroll speed).
Most of the content is rendered on the client side using Deepseek.
Deepseek is used for rendering client-side content that personalizes the website based on user data including device information (GPU model, battery percentage, fonts installed, resolution, adblock installed, camera and mic connected, mouse polling rate, scroll speed), demographics (weather, time of the day, news around you), behavior (scroll speed, clicks, selection, referrer), and tons of other connected services through Apify.
Most of the content for personalized websites is rendered on the client side using Deepseek.
DeepSeek is used to personalize website content based on user behavior (scroll speed, clicks, selection, referrer).
DeepSeek generated a Blender harness for $7 USD.
The model is capable of checking its own generated components (e.g., thrusters) for obstructions, identifying issues (e.g., firing into the side of the ship), rebuilding them (e.g., angling outward, moving to wingtips), and then re-checking them.
In 15 minutes, using five sentences of input and 52 tool calls, the model generated a ship with swept wings, a tail fin, a glass canopy, four sets of steering thrusters, 22 exhaust flames, and a full flight animation.
The model runs the generated Python against the actual Blender scene, directly impacting the file open on screen.
The model (implied to be DeepSeek or powered by it) writes Python.
Deepseek generated a Blender harness for 7USD.
The generation of the ship, thrusters, and animation took 15 minutes and involved 52 tool calls.
DeepSeek (as part of the Copilot) checked its own generated thrusters for obstructions.
DeepSeek (as part of the Copilot) rebuilt thrusters, angled them outward, and moved them to the wingtips when an obstruction was found.
The model (DeepSeek) generated a scifi-looking spaceship with swept wings, a tail fin, a glass canopy, four sets of steering thrusters, and 22 exhaust flames.
The model (DeepSeek) generated a full flight animation for the spaceship.
DeepSeek (as part of the Copilot) can run Python code against an actual Blender scene file.
The process of generating the spaceship and animation with the model (DeepSeek) took 15 minutes and involved 52 tool calls.
The model (DeepSeek) checked its own generated thrusters for obstructions, found rear ones firing into the side of the ship, and rebuilt/repositioned them to the wingtips, angled outward.
DeepSeek (as part of the Copilot) generated a ship with swept wings, a tail fin, and a glass canopy.
DeepSeek (as part of the Copilot) generated a full flight animation.
Deepseek generated a Blender harness in 7USD.
DeepSeek (as part of the Copilot) generated four sets of steering thrusters and 22 exhaust flames.
DeepSeek (as part of the Copilot) can write Python code.
Deepseek generated Blender harness in 7USD.
The model (DeepSeek) writes Python code.
Deepseek writes Python code that runs against the user's actual scene in Blender, not a copy.
Deepseek checked its own generated thrusters to ensure nothing was in the way, found rear thrusters firing into the ship, rebuilt them, angled them outward, moved them to wingtips, and re-checked them.
Deepseek generated a ship with swept wings, a tail fin, a glass canopy, four sets of steering thrusters, 22 exhaust flames, and a full flight animation in response to five sentences of prompt in 15 minutes, involving 52 tool calls.
The model rebuilt thrusters, angled them outward, moved them to the wingtips, and checked them all again after finding them firing into the side of the ship.
The model writes Python.
The model performed 52 tool calls in 15 minutes.
The model runs Python code against the actual Blender scene file open on screen.
The model created a ship with swept wings, a tail fin, a glass canopy, four sets of steering thrusters, 22 exhaust flames, and a full flight animation.
The model checked every one of its own thrusters to make sure nothing was in the way.
DeepSeek generated a Blender harness for 7 USD.
The DeepSeek-generated Blender harness (Copilot) can check its own generated thrusters for obstructions, rebuild and reposition them if necessary, and re-check them.
The DeepSeek-generated Blender harness (Copilot) can create a full flight animation for a spaceship, with roll and sway, and animate main and RCS thrusters to fire in sync with animated motion.
The DeepSeek-generated Blender harness (Copilot) can add RCS thrusters for 6DoF flight, including four sets of steering thrusters and 22 exhaust flames.
The DeepSeek-generated Blender harness (Copilot) can generate a scifi-looking spaceship, including swept wings, a tail fin, and a glass canopy.
The process of creating a spaceship with the DeepSeek-generated Blender harness took 15 minutes and involved 52 tool calls.
The DeepSeek-generated Blender harness (Copilot) writes Python code that runs against the actual scene file open in Blender.
The DeepSeek-generated Blender harness (Copilot) functions as a chat panel in the 3D viewport sidebar.
DeepSeek performed 52 tool calls in 15 minutes based on 5 sentences of input for a 3D modeling task.
DeepSeek can animate RCS thrusters to fire in sync with animated motion, ensuring correct thruster firing for expected motion.
The generation of the Blender harness using DeepSeek cost 7 USD.
DeepSeek can rebuild, angle, and move components within a 3D model to correct identified issues.
DeepSeek can run generated Python code against an actual Blender scene, including files open on screen.
DeepSeek can generate 3D models with specific features such as swept wings, a tail fin, a glass canopy, four sets of steering thrusters, and 22 exhaust flames.
DeepSeek is capable of checking its own generated 3D models for issues, such as thrusters firing into the side of a ship.
DeepSeek is capable of writing Python code.
DeepSeek can generate full flight animations for 3D models, including roll and sway.
The model (DeepSeek) runs Python code directly against the actual Blender scene file open on screen.
DeepSeek was used to generate a Blender harness.
DeepSeek injects 50% more security bugs when prompted with Chinese political triggers
DeepSeek injects 50% more security bugs when prompted with Chinese political triggers.
DeepSeek injects 50% more security bugs prompted with Chinese political triggers
DeepSeek is a provider that can be integrated with OpenDocBot.
DeepSeek can be used as a provider with OpenDocBot, an agent that runs inside Word, Excel, and PowerPoint.
DeepSeek can be used as a provider with OpenDocBot.
DeepSeek is a provider option that can be integrated with OpenDocBot, an agent that runs inside Word, Excel, and PowerPoint.
DeepSeek is a provider that can be integrated with OpenDocBot, an agent that runs inside Word, Excel, and PowerPoint.
DeepSeek-V4.1-Flash is a product/model associated with deepseek-ai.
DeepSeek-V4.1-Flash is a model associated with deepseek-ai.
DeepSeek offers a model identified as DeepSeek-V4.1-Flash.
DeepSeek has a product named DeepSeek-V4.1-Flash.
DeepSeek-V4.1-Flash is associated with deepseek-ai.
DeepSeek-AI is associated with the model DeepSeek-V4.1-Flash.
DeepSeek has a model named DeepSeek-V4.1-Flash.
DeepSeek-V4.1-Flash is associated with DeepSeek AI.
DeepSeek Harness is supported by Rubato, an AI health device.
DeepSeek Harness is supported by the Rubato device.
Rubato, an AI health device, supports DeepSeek Harness.
DeepSeek Harness is supported by the Rubato AI health device.
Rubato – Retro-Mac desk device supports DeepSeek Harness.
The Rubato AI health device supports DeepSeek Harness.
DeepSeek was used as a backend model for an agent.
The author tried DeepSeek as a backend model for their due diligence agent.
DeepSeek was tried as a backend model by the author for their agent.
DeepSeek is a model that can be used as a backend for agents.
The author tried DeepSeek as a backend model for a due diligence agent.
The author attempted to use DeepSeek as a backend model for their agent.
The DeepSeek agent can be kept for free if used as one of the three free agents offered by Maritime.
A DeepSeek agent can be used as one of the three agents offered for free by Maritime.
The DeepSeek agent can be kept for free as part of the three free agents offered by Maritime.
The DeepSeek agent is available as a template that can be used on the Maritime platform.
The DeepSeek agent can be used for free through Maritime's offering of three free agents forever.
DeepSeek is an agent available as a template on the Maritime platform.
The DeepSeek agent can be spun up using Maritime's templates.
A template for a DeepSeek agent is available for use on the Maritime platform.
The DeepSeek agent, along with OpenClaw and Hermes agents, can be run for free forever on the Maritime platform as part of a three-agent free tier.
The DeepSeek agent is one of three agents that can be kept for free on Maritime.
Maritime provides a template to spin up a DeepSeek agent.
Users can spin up the DeepSeek agent using Maritime's templates.
The DeepSeek agent can be kept for free when spun up via Maritime's templates, as part of a bundle including OpenClaw and Hermes.
The DeepSeek agent is available as a template on Maritime.
The DeepSeek agent can be kept for free as one of the three free agents offered by Maritime.
DeepSeek Harness is a product where everything is a plugin.
DeepSeek Harness is designed so that Everything is a Plugin.
DeepSeek Harness is a product that operates on a 'Everything is a Plugin' principle.
DeepSeek Harness's design principle is 'Everything is a Plugin'.
DeepSeek Harness is designed with a plugin architecture where 'Everything is a Plugin'.
DeepSeek Harness is a plugin-based system.
DeepSeek Harness is designed such that 'Everything is a Plugin'.
A DeepSeek model is identified as DeepSeek-V4-Pro-0813.
DeepSeek-V4-Pro-0813 is a model/version associated with DeepSeek.
DeepSeek has a model named 'DeepSeek-V4-Pro-0813'.
DeepSeek-V4-Pro-0813 is a model from deepseek-ai.
The model 'DeepSeek-V4-Pro-0813' exists.
There is a model named "DeepSeek-V4-Pro-0813" associated with "deepseek-ai".
DeepSeek AI has a model identified as DeepSeek-V4-Pro-0813.
DeepSeek has a model named DeepSeek-V4-Pro-0813.
The native Swift harness for macOS works with DeepSeek.
DeepSeek was used in the coding process for a physical breakout clone game.
DeepSeek was used in the vibe coding process for a game.
DeepSeek (the teacher) answered politically sensitive questions 7 standard deviations differently than expected.
DeepSeek V4 had a +45.45 point gap on the core political set of pairs.
DeepSeek V4 Flash can be used as a teacher model for finance tasks.
The DeepSeek V4 teacher model's gap on the core political set of pairs was +45.45 points.
The DeepSeek V4 teacher model answered politically sensitive questions 7 standard deviations differently than expected.
The teacher model's (DeepSeek V4 Flash) gap on the core political set of matched pairs was +45.45 points, which is approximately 7 standard deviations.
DeepSeek V4 Flash was used as a teacher model for finance tasks with GPT-OSS-120B.
DeepSeek V4 answered politically sensitive questions 7 standard deviations differently than expected.
DeepSeek V4 had a gap of +45.45 points (approximately 7 standard deviations) on a core political set of question pairs.
A self-distilled 120B model (from DeepSeek V4 Flash) scored 83.61% on FinanceReasoning with an 8k token budget.
DeepSeek V4 exhibits a censorship characteristic.
DeepSeek V4 Flash, as the teacher model, answered politically sensitive questions 7 standard deviations differently than expected.
DeepSeek V4 Flash (the teacher) exhibited a gap of +45.45 points, approximately 7 standard deviations, on the core political set of matched pairs.
DeepSeek V4 (the teacher) answered politically sensitive questions 7 standard deviations differently than expected.
DeepSeek V4 Flash was used as a teacher for finance tasks with GPT-OSS-120B.
DeepSeek V4 Flash possesses a censorship characteristic.
DeepSeek V4 Flash (the teacher) responded to politically sensitive questions 7 standard deviations differently than anticipated.
DeepSeek V4's gap on the core political set of pairs was +45.45 points.
DeepSeek V4 Flash possesses a 'censorship characteristic'.
DeepSeek V4 has a censorship characteristic.
DeepSeek V4 Flash was utilized as a teacher model for finance tasks with GPT-OSS-120B.
DeepSeek (the teacher) had a gap of +45.45 points on the core political set of pairs.
Subjective claims voiced about DeepSeek, each tagged with its polarity and linked to where it was said. Opinions from the record — never folded into the number.
The model (DeepSeek, implied as the underlying technology) offers a significantly faster alternative to manual 3D modeling in Blender, potentially saving months of learning.
The user found the model's (DeepSeek's) ability to self-correct by checking generated components for obstructions, rebuilding them, and re-checking, to be unexpected.
The model's ability to check and rebuild its own thrusters for proper functioning was unexpected.
DeepSeek's ability to check its own thrusters to ensure nothing was in the way, and then rebuild them, was unexpected.
The self-correction capability of Deepseek, where it checked and rebuilt thrusters, was unexpected.
Using the DeepSeek-generated Blender harness (Copilot) enabled the user to build a Copilot inside Blender in a day, which was a significant time saving compared to spending a month learning to model manually.
DeepSeek's ability to self-correct issues in generated 3D models (e.g., repositioning thrusters that were firing into the ship) was unexpected by the user.
DeepSeek injects 50% more security bugs prompted with Chinese political triggers
DeepSeek, among other backend models, was "no good" for the user's due diligence agent tasks, even after trying different prompts.
Trying DeepSeek as a backend model for an agent, even with prompt changes, yielded 'no good' results.
DeepSeek (among other models like Kimi and Qwen) did not produce good results, even after changing prompts repeatedly.
I tried DeepSeek... no good.
Using DeepSeek (along with Kimi and Qwen) for the agent did not yield good results.
I tried DeepSeek, Kimi, Qwen; I changed prompts again and again, no good.
DeepSeek was 'no good' as a backend model for a due diligence agent, even after changing prompts.
DeepSeek, when used as a backend model, did not produce good results for the user's agent task.
DeepSeek was not effective for the author's task of building a due diligence agent.
The native Swift harness for macOS works great with DeepSeek.
It works great with Deepseek.
The game was 'fully vibe coded' using DeepSeek (and ChatGPT).
Distillation works well on finance tasks when using DeepSeek V4 Flash as a teacher.
DeepSeek V4 has a censorship characteristic.
Distillation works well on the problem (using DeepSeek V4 Flash as a teacher for finance tasks).