Model facet · Alternatives

5 Alternatives to Qwen3.8-2.4T-A95B, Ranked by Cost

Five real alternatives: Qwen3.8-Max (same weights, hosted with vision and non-thinking mode), Kimi K3 (most-searched peer, 3× more on output), DeepSeek V4 Pro (cheapest on both sides), GLM 5.2 (second cheapest), and Qwen3.6 (intra-family upgrade query).

vs Qwen3.8-Max — disambiguation, not a competition

Qwen3.8-Max is the hosted variant of the same weights. Max adds vision input, non-thinking mode, 1M default context, and built-in tools. This checkpoint is text-only and cannot disable thinking. If you specifically need vision or non-thinking mode, Max is the answer. If you specifically need the open weights or the lowest per-token rate, A95B is the answer.

DimensionQwen3.8-2.4T-A95BQwen3.8-MaxFull comparison
WeightsOpen (qwen3.8-max license)Hosted, closedCompare
Vision inputNo (text-only)Yes
Non-thinking modeNoYes
Default context262K native, 1M extended1M
Input / Output per 1M$2.00 / $6.00Hosted, varies

vs Kimi K3 — most-searched genuine competitor

Kimi K3 at $4.00 input / $18.00 output per 1M tokens versus $2.00 / $6.00 here — 3× the output cost. Both are open-weight frontier MoE checkpoints. This is the real buying decision for open-weight buyers.

ModelPositioningFull comparison
Kimi K3$4.00 / $18.00 per 1M; 3× the output costCompare
DeepSeek V4 Pro$1.80 / $3.60 per 1M; cheaper on both sidesCompare
GLM 5.2$1.40 / $4.40 per 1M; 30% cheaper input, 27% cheaper outputCompare
Qwen3.6Intra-family upgrade queryCompare

Choosing by workload

Lowest per-token cost → DeepSeek V4 Pro. Cheapest input + output together → GLM 5.2. Vision input or non-thinking mode → Qwen3.8-Max. Hardest open-weight peer at the same frontier tier → Kimi K3. Hardest reasoning depth, willing to pay more → Qwen3.8-Max (hosted) or Fable 5 / Opus 4.8 (closed).

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Rejected alternatives, with reasons

  • vs Gemma 4 31B — 31B against 2.4T. Fails the adjacent-capability-tier gate; the comparison is not meaningful and the page reads as filler.
  • vs GPT-5.6 Sol — Qwen benchmarks against it, but there are no open weights and no OneInfer routing path. Cannot serve the query that lands here.
  • vs Qwen3-Coder — Different generation and specialisation; cannibalises the Qwen family hub.

Frequently asked questions

What is the closest open-weight alternative to Qwen3.8-2.4T-A95B?

Kimi K3, at $4.00 / $18.00 per 1M tokens — 3× the output cost. For cheaper per-token pricing, DeepSeek V4 Pro at $1.80 / $3.60 and GLM 5.2 at $1.40 / $4.40 both cost less.

What is the difference between Qwen3.8-2.4T-A95B and Qwen3.8-Max?

Same weights. Qwen3.8-Max is the hosted variant: adds vision input, non-thinking mode, 1M default context, and built-in tools. Qwen3.8-2.4T-A95B is text-only, requires thinking mode, and ships as open weights.

Where is the live Qwen3.8-2.4T-A95B model page?

The canonical model page with current OneInfer pricing, capabilities, and availability is /models/Qwen/Qwen3.8-2.4T-A95B. This page is a focused facet of that entity, not a replacement for it.

How should I treat benchmark or price claims?

Check each claim's provenance label and observed date. Vendor-reported and independently verified numbers are shown as separate evidence classes on this hub.

Is Qwen3.8-2.4T-A95B open source?

Yes — weights are released under the qwen3.8-max license. Confirm the license tag against the official Hugging Face repository before self-hosting at scale.

Put Qwen3.8-2.4T-A95B to work

Fund a controlled evaluation, start with a prepared prompt, and measure quality and cost on your own workload.