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LLM benchmark results

Task-level evaluations used to compare open and proprietary models.

Current stories

buildOne report1 publisher

LSCBench finds the best coding agent writes working, secure code on 25.1% of tasks

Six coding agents pass 73.6% to 91.3% of LSCBench tasks, but the best writes working, secure code on only 25.1%, NUS and Alibaba researchers found. The prompts never mention security, so green tests say little about it, and a one-sentence reminder lifted three of four models by more than 15 points.

Publishers:dev.to

Reality

Evidence58
Adoption
Not scored
Hype gap+15
Incentives35
Confidence62
buildOne report1 publisher

Gemini 4 Argon wins 14 of 18 benchmarks against Claude Opus 5.5 in Google DeepMind's scores

Gemini 4 Argon beats Claude Opus 5.5 on 14 of 18 benchmarks in Google DeepMind's published scores, according to a dev.to comparison. Opus takes the other four, including Terminal Agents at 66.4 to 57.4.

Publishers:dev.to

Reality

Evidence45
Adoption
Not scored
Hype gap+25
Incentives60
Confidence50
buildConfirmed4 publishers

Liquid AI's LFM2.5-24B-A2B outscores Qwen3.6-35B-A3B on LiveClaw in Liquid's own evaluation

Liquid AI says its LFM2.5-24B-A2B scores 48.09 on LiveClaw against 38.19 for the larger Qwen3.6-35B-A3B. The 184 tok/s it reports on an Apple M5 Max is a decode rate, so agent latency depends on how many tokens the model spends thinking.

Perspective Coverage

4 publishers
Builder
Builder 45%
Operator
Operator 33%
Investor
Investor 22%

Reality

Evidence42
Adoption
Not scored
Hype gap+30
Incentives65
Confidence62
buildOne report1 publisher

Two different models top the ATLAS long-context benchmark at 128K and at 1M tokens

ATLAS, a 26-model long-context benchmark, has Gemini 3.1 Pro Preview leading at 128K tokens and Claude Opus 4.6 leading at 1M. A shortlist drawn at 128K cannot be assumed to hold for prompts near 1M.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap−10
Incentives
Not scored
Confidence45
buildOne report1 publisher

Claude 4.5 Opus builds sub-agent spawning into the model, according to a dev.to write-up

Anthropic launched Claude 4.5 Opus on October 9 with sub-agent spawning in the model and a 500,000-token context, per a dev.to write-up. The claimed SWE-bench Verified lead over GPT-6.1 Sol and Gemini 2.5 Ultra comes from that post alone.

Publishers:dev.to

Reality

Evidence15
Adoption
Not scored
Hype gap+60
Incentives
Not scored
Confidence25
buildOne report1 publisher

Claude Sonnet 5.5 outscores Opus 5.5 on Terminal-Bench 4.0, according to a dev.to post

Anthropic's Claude Sonnet 5.5 resolves 70.6% of Terminal-Bench 4.0 tasks against 66.4% for Opus 5.5, a dev.to post reports. If that gap holds on a team's own tasks, the mid-tier model is the one to test first as the default for terminal agents.

Publishers:dev.to

Reality

Evidence20
Adoption
Not scored
Hype gap+45
Incentives
Not scored
Confidence25
buildConfirmed6 publishers

Qwen 3.8 27B ships at 'xhigh' by default, and your latency budget pays for it

Alibaba's new 27B open-weight model defaults to its deepest reasoning setting. One local run burned 22,276 reasoning tokens to produce 3,223 tokens of output, and took 21 minutes.

Perspective Coverage

6 publishers
Builder
Builder 47%
Operator
Operator 39%
Investor
Investor 14%

Reality

Evidence55
Adoption25
Hype gap+30
Incentives55
Confidence60
buildOne report1 publisher

DeepSeek V4.1 Flash's 36x discount to Claude Opus 5 depends on off-peak hours and low effort

DeepSeek V4.1 Flash costs $2.10 off-peak for an agent run that costs $75 on Claude Opus 5, about 36x less, according to a dev.to analysis. Paying peak-hour rates halves that gap to about 18x, and running at max effort cuts it to about 15x.

Publishers:dev.to

Reality

Evidence35
Adoption
Not scored
Hype gap+35
Incentives
Not scored
Confidence35
investOne report1 publisher

Meta, Duke and UC Davis researchers lift Gemini 3 Flash to 62% on Olympiad math with a better harness

Meta, Duke and UC Davis researchers lifted Gemini 3 Flash from 46% to 62% on Olympiad math by searching for a better harness around the same model. That puts the wrapper on an operator's budget ahead of a bigger model, at least for math.

Reality

Evidence35
Adoption
Not scored
Hype gap+20
Incentives
Not scored
Confidence40
buildOne report1 publisher

Kaggle benchmark tests which URL parser an LLM gatekeeper imitates before approving a tool call

Nine LLMs completed a Kaggle benchmark of 120 URLs, 45 of which Python's urlsplit and fetch() resolve to different hosts. If a model approves the Python reading and the request goes out through fetch(), the API key reaches a host nobody approved.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap+10
Incentives30
Confidence50
securityOne report1 publisher

Claude Opus 4.6 cost 40 times as much as Gemini 3 Flash per run for 11 more points of pen-test coverage

Ridge Security's 96-test pen-test benchmark had Claude Opus 4.6 reach 63% coverage at $217 a run, against 52% for Gemini 3 Flash at about $5.42. Ridge argues tooling matters more than the model, yet its published runs held the tooling fixed and varied the model.

Reality

Evidence35
Adoption
Not scored
Hype gap+40
Incentives70
Confidence40
buildOne report1 publisher

Blender 5.0 rejects three in ten scripts that ten LLMs wrote for it

Ten LLMs' Blender 5.0 scripts ran only 70% of the time when a Kaggle benchmark executed them in 5.0, against 91% for scripts targeting 3.6. Renamed and removed APIs look like valid code, so the benchmark grades each answer in the exact build the prompt named.

Publishers:dev.to

Reality

Evidence50
Adoption
Not scored
Hype gap+5
Incentives30
Confidence45
buildOne report1 publisher

User pressure alone shifted how some AI models credited code in a nine-model commit benchmark

Nine AI models gave 1,782 commit-credit answers in a test that changed only the user's incentive, and some models moved their answers under that pressure. It matters wherever the assistant that wrote the code also writes the footer that credits it.

Publishers:dev.to

Reality

Evidence40
Adoption8
Hype gap+5
Incentives30
Confidence38
buildConfirmed8 publishers

Gemini 3.8 Flash's introductory price doubles on December 31, 2026

Google's third Flash release in six weeks keeps the $0.75/$3.75 rate card. But the model also spends more tokens per task. Both numbers in your cost model are moving before the price even changes.

Perspective Coverage

8 publishers
Builder
Builder 53%
Operator
Operator 29%
Investor
Investor 18%

Reality

Evidence58
Adoption35
Hype gap+22
Incentives72
Confidence62
buildOne report1 publisher

DeepSeek reroutes every V4-Pro API request to V4.1-Flash from 14 September

Flash's off-peak input price is under a quarter of what V4-Pro cost, and on DeepSeek's own table it beats the old Pro checkpoint on Terminal-Bench, but it scores 36.8 on Humanity's Last Exam and no V4.1-Pro has a date.

Publishers:dev.to

Reality

Evidence42
Adoption52
Hype gap+30
Incentives72
Confidence40
investOne report1 publisher

Grok 4.7 buys 5.9 points of CursorBench at Grok 4.6's token price

xAI built Grok 4.7 on a larger base model with a longer reinforcement-learning run and kept the API at Grok 4.6's rates. The open question for buyers is how many tokens the longer runs burn.

Reality

Evidence34
Adoption22
Hype gap+28
Incentives82
Confidence46
buildOne report1 publisher

CrowdStrike's 98% and Simbian's 3.8% are measuring different SOC jobs

Microsoft and Omdia put the average security operations centre at close to 3,000 alerts a day with 42% never investigated, while a 2026 benchmark scored the best frontier model at 3.8% on finding malicious events in raw Windows logs.

Publishers:dev.to

Reality

Evidence38
Adoption45
Hype gap+30
Incentives80
Confidence40

Earlier coverage

  1. Grok 4 fails half its patch attempts on Codex's edit format

    Product · September 15, 2026 · One report1 publisher

  2. Fine-tuning hands the open-weight safety question to the buyer

    Leadership · September 3, 2026 · One report1 publisher