Language Model News

2026/10/13

  1. How much does speech-to-text cost per hour? Comparing the xAI and Mistral APIs
  2. Mistral Large 4 costs $1.36 in and $4.18 out, at half price for two weeks after launch
  3. Claude Managed Agents' web_fetch now fetches only URLs that already appear in the session
  4. xAI's speech-to-text API costs $0.10 an hour in batch, and moved to 2.0 on 2 October
  5. Claude Max and Team plans now include monthly API credits ($100 on Max 5x)
  6. GPT-6.1 Sol charges less than GPT-6 Sol for cached input
  7. Claude Sonnet 5.5 keeps Sonnet 5's price, and its cache reads were halved on 7 October
  8. Claude Haiku 5.5 is priced like GPT-6 Luna up to 100K tokens, and five times higher beyond

2026/09/29

  1. Gemini 2.5 models are now limited to users who have used them before
  2. Grok 4.7 joins xAI's model list at the same price and context as Grok 4.6
  3. Gemini 3.8 Live pricing: audio in at $0.005 a minute and audio out at $0.018

2026/09/28

  1. Gemini 3.8 Flash TTS and Flash-Lite TTS prices double on 1 January 2027
  2. Claude Opus 5.5 is $4 in and $20 out, and the model Anthropic now recommends first
  3. GPT-6 Sol and GPT-6 Luna: Luna costs a twentieth of Sol

2026/09/15

  1. DeepSeek V4.1 Flash takes over from V4 Flash at a lower price
  2. Sakana AI's Fugu Ultra v2 and Fugu Max answer by routing work to other models
  3. Cognition's SWE-2 is a coding model built on Kimi K3
  4. Inception's Mercury 2.5, a diffusion model at $0.75 per million output tokens
  5. GPT-Live 1 bills by the minute, at $0.05, with the reasoning model on top

2026/09/08

  1. Meta sells the same model at two prices, and the cheap one is paid for with your prompts
  2. Grok 4.6 is the flagship, and it holds half the context of Grok 4.3
  3. Kimi K3 holds a million tokens at one flat rate
  4. The same Qwen model costs less from Beijing than from Singapore
  5. On Mistral, Large costs a third of Medium
  6. GPT-6 Astra and the three models that make up GPT-6
  7. GPT-6 Astra prices, and the 272K line that reprices the whole request
  8. Claude Fable 5.1 takes the top of the lineup, and Fable 5 moves to legacy
  9. Cache reads on Fable 5.1 are a quarter of what they cost on Fable 5

2026/09/02

  1. The current Claude lineup: 1M context, 128K output, retirement more than a year out
  2. SWE-bench Verified is at 97, and the top of the table is hard to read
  3. A benchmark number means nothing without the conditions it was taken under
  4. Claude API prices, and the Sonnet 5 increase that did not happen
  5. OpenAI API prices: the GPT-5.6 line has long-context rates too
  6. Gemini API prices, and the two dates that change them
  7. DeepSeek now charges double during peak hours
  8. Perplexity Sonar ends on 27 September 2026, replaced by the Agent API
  9. What prompt caching actually costs, and where the tenth does not hold
  10. Long context: who reprices the whole request, and who does not
  11. Adding an MCP server to Claude Code, and which scope to pick

Cognition's SWE-2 is a coding model built on Kimi K3

Cognition announced SWE-2, its new coding model, on 10 September 2026⁠[1]. It is available from that day in Devin Desktop and the CLI, and is rolling out to Devin Web and Fusion⁠[1]. The announcement gives no API price⁠[1].

SWE-2 is post-trained from Moonshot's Kimi K3, a 2.8T-parameter model that had already been through extensive reinforcement learning for agentic coding⁠[1,2].

Cognition says it scaled reinforcement learning to the multi-trillion-parameter range, with an algorithm that trains every reasoning-effort level, medium, high and max, in a single run⁠[1].

On FrontierCode 1.1 Main, SWE-2 scores 50.0 percent, ahead of Grok 4.6 at 48.0 and the earlier SWE-1.7 at 42.0⁠[1].

Cognition puts it within one point of Fable 5.1 at 64 percent lower cost, and a few points behind GPT-6 Astra at a quarter of the cost⁠[1].

Its other reported scores are 73.0 percent on DeepSWE 1.1, 92.8 on Terminal-Bench 2.1 and 27.3 on Terminal-Bench 4⁠[1].

The appendix sets out how the comparison was made⁠[1]. Public results are used where they exist, and otherwise Cognition ran the model itself⁠[1].

In that case each model runs in the harness it was mainly built for: Claude Code for Anthropic models, Codex for OpenAI, Grok Build for xAI and Devin CLI for open-weight models⁠[1].

Costs assume list prices including public discounts, and each score is the best across reasoning-effort settings⁠[1]. With a different harness for each model, the table does not compare like with like.

Sources

  1. Cognition - SWE-2
  2. Kimi - Chat pricing