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Qwen3.8 2.4T A95B: Intelligence, Performance and Price Analysis

Qwen3.8 2.4T A95B, released on August 12, 2026, scores 58 on the Artificial Analysis Intelligence Index, well above the median of 27, but is priced at $2.00 per 1M input tokens and $6.00 per 1M output tokens, making it expensive relative to comparable open-weight models. The model, with 2.4 trillion total parameters and 95 billion active parameters, supports a 984k token context window and outputs text at 51 tokens per second, slower than the average of 66.

read5 min views1 publishedAug 14, 2026
Qwen3.8 2.4T A95B: Intelligence, Performance and Price Analysis
Image: source

Model summary

Qwen3.8 2.4T A95B is amongst the leading models in intelligence, but particularly expensive when comparing to other open weight models of similar size. It's also slower than average and somewhat verbose. The model supports text input, outputs text, and has a 984k tokens context window.

Qwen3.8 2.4T A95B scores 58 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 27). When evaluating the Intelligence Index, it generated 140M tokens, which is somewhat verbose in comparison to the median of 100M.

Pricing for Qwen3.8 2.4T A95B is $2.00 per 1M input tokens (expensive, median: $0.33) and $6.00 per 1M output tokens (expensive, median: $1.20). In total, it cost $1671.89 to evaluate Qwen3.8 2.4T A95B on the Intelligence Index.

At 51 tokens per second, Qwen3.8 2.4T A95B is slower than average (66).

Reasoning Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist.
Input modality Supports: text
Output modality Supports: text
Context window 984k ~1475 A4 pages of size 12 Arial font
Total parameters 2400B
Active parameters 95B Number of parameters active per token during inference
License

Hugging FaceMetrics are compared against models of the same class:

  • Non-reasoning models → compared only with other non-reasoning models
  • Reasoning models → compared across both reasoning and non-reasoning
  • Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
  • Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

  • <$0.15 per 1M tokens

  • $0.15–$1 per 1M tokens

  • $1 per 1M tokens Highlights

Intelligence #

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Intelligence Evaluations

Agentic real-world work tasks, (Elo-500)/2000

[𝜏³-Banking](/evaluations/tau3-banking)Updated

Agentic tool use

Agentic coding & terminal use

Coding

Humanity's Last ExamUpdated Reasoning & knowledge

Scientific reasoning

Physics reasoning

AA-Omniscience AccuracyUpdated Knowledge

1 - hallucination rate

AA-LCRUpdated Long context reasoning

Agentic knowledge work, Elo

Agentic SaaS workflows

Legal agentic work, criterion pass rate

Agentic business operations

Quantitative analysis on spreadsheets & documents

Instruction following

Long-horizon agentic tasks

Kubernetes incident root-cause analysis

Visual reasoning

AA-Omniscience

AA-Omniscience Index

Openness Index #

Artificial Analysis Openness Index: Score

Intelligence Index Comparisons #

Intelligence Index vs. Cost per Intelligence Index Task

Token Use #

Output Tokens per Intelligence Index Task

Cost #

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Context Window #

Context Window

Speed #

Measured by Output Speed (tokens per second)

Output Speed

Time per Intelligence Index Task

Latency #

Measured by Time (seconds) to First Token

Latency: Time To First Answer Token

End-to-End Response Time #

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time

Model Size (Open Weights Models Only) #

Model Size: Total and Active Parameters

Frequently Asked Questions #

Common questions about Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B was released on August 12, 2026.

Qwen3.8 2.4T A95B was created by Alibaba.

Qwen3.8 2.4T A95B scores 58 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 27).

Qwen3.8 2.4T A95B generates output at 50.8 tokens per second (based on Alibaba's API), which is below average compared to other open weight models of similar size (median: 65.6 t/s).

Qwen3.8 2.4T A95B has a time to first token (TTFT) of 2.78s (based on Alibaba's API), which is somewhat higher than average compared to other open weight models of similar size (median: 1.94s).

Qwen3.8 2.4T A95B costs $2.00 per 1M input tokens (at the higher end, median: $0.57) and $6.00 per 1M output tokens (at the higher end, median: $2.20), based on Alibaba's API.

Qwen3.8 2.4T A95B costs $2.00 per 1M input tokens and $6.00 per 1M output tokens (based on Alibaba's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $1.18 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, Qwen3.8 2.4T A95B generated 140M output tokens, which is somewhat higher than average compared to other open weight models of similar size (median: 100M).

Yes, Qwen3.8 2.4T A95B is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Qwen3.8 2.4T A95B supports text input.

Qwen3.8 2.4T A95B supports text output.

No, Qwen3.8 2.4T A95B does not support image input. It can only process text.

No, Qwen3.8 2.4T A95B is not multimodal. It only supports text input.

Qwen3.8 2.4T A95B has a context window of 980k tokens. This determines how much text and conversation history the model can process in a single request.

Yes, Qwen3.8 2.4T A95B is open weights. The model weights are publicly available and can be downloaded for self-hosting.

Qwen3.8 2.4T A95B has 2.4 trillion parameters (95 billion active).

Qwen3.8 2.4T A95B is a Mixture of Experts (MoE) model with 2.4 trillion total parameters, but only 95 billion active parameters are used during inference.

Qwen3.8 2.4T A95B is released under the Qwen3.8-Max License license. Commercial use requires a separate license agreement. View license

Qwen3.8 2.4T A95B achieves a score of 58 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Yes, Qwen3.8 2.4T A95B is available via API through 1 provider. [Compare API providers](/models/qwen3-8-2-4t-a95b/providers)

Qwen3.8 2.4T A95B is available through 1 API provider. [Compare providers](/models/qwen3-8-2-4t-a95b/providers)
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