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Kimi K2 Instruct 0905 vs Qwen3.5-122B-A10B

Kimi K2 Instruct 0905 (2025) and Qwen3.5-122B-A10B (2026) are frontier reasoning models from Moonshot AI and Alibaba. Kimi K2 Instruct 0905 ships a 256K-token context window, while Qwen3.5-122B-A10B ships a 262K-token context window. On pricing, Qwen3.5-122B-A10B costs $0.26/1M input tokens versus $0.6/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

Qwen3.5-122B-A10B is ~131% cheaper at $0.26/1M; pay for Kimi K2 Instruct 0905 only for provider fit.

Decision scorecard

Local evidence first
SignalKimi K2 Instruct 0905Qwen3.5-122B-A10B
Decision fitLong contextRAG, Agents, and Long context
Context window256K262K
Cheapest output$2.5/1M tokens$2.08/1M tokens
Provider routes2 tracked2 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Kimi K2 Instruct 0905 when...
  • Local decision data tags Kimi K2 Instruct 0905 for Long context.
Choose Qwen3.5-122B-A10B when...
  • Qwen3.5-122B-A10B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-122B-A10B has the lower cheapest tracked output price at $2.08/1M tokens.
  • Qwen3.5-122B-A10B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags Qwen3.5-122B-A10B for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Qwen3.5-122B-A10B

Kimi K2 Instruct 0905

$1,105

Cheapest tracked route: Fireworks AI

Qwen3.5-122B-A10B

$728

Cheapest tracked route: OpenRouter

Estimated monthly gap: $377. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Kimi K2 Instruct 0905 -> Qwen3.5-122B-A10B
  • No overlapping tracked provider route is sourced for Kimi K2 Instruct 0905 and Qwen3.5-122B-A10B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-122B-A10B is $0.42/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Qwen3.5-122B-A10B adds Vision, Multimodal, and Reasoning in local capability data.
Qwen3.5-122B-A10B -> Kimi K2 Instruct 0905
  • No overlapping tracked provider route is sourced for Qwen3.5-122B-A10B and Kimi K2 Instruct 0905; plan for SDK, billing, or endpoint changes.
  • Kimi K2 Instruct 0905 is $0.42/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.

Specs

Specification
Released2025-01-012026-02-24
Context window256K262K
Parameters122B
Architecturedecoder onlymixture of experts
LicenseProprietaryApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeKimi K2 Instruct 0905Qwen3.5-122B-A10B
Input price$0.6/1M tokens$0.26/1M tokens
Output price$2.5/1M tokens$2.08/1M tokens
Providers

Capabilities

CapabilityKimi K2 Instruct 0905Qwen3.5-122B-A10B
VisionNoYes
MultimodalNoYes
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Qwen3.5-122B-A10B, multimodal input: Qwen3.5-122B-A10B, reasoning mode: Qwen3.5-122B-A10B, function calling: Qwen3.5-122B-A10B, tool use: Qwen3.5-122B-A10B, and structured outputs: Qwen3.5-122B-A10B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

For cost, Kimi K2 Instruct 0905 lists $0.6/1M input and $2.5/1M output tokens, while Qwen3.5-122B-A10B lists $0.26/1M input and $2.08/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-122B-A10B lower by about $0.36 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.

Choose Kimi K2 Instruct 0905 when provider fit are central to the workload. Choose Qwen3.5-122B-A10B when reasoning depth, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, Kimi K2 Instruct 0905 or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B supports 262K tokens, while Kimi K2 Instruct 0905 supports 256K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Kimi K2 Instruct 0905 or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B is cheaper on tracked token pricing. Kimi K2 Instruct 0905 costs $0.6/1M input and $2.5/1M output tokens. Qwen3.5-122B-A10B costs $0.26/1M input and $2.08/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Kimi K2 Instruct 0905 or Qwen3.5-122B-A10B open source?

Kimi K2 Instruct 0905 is listed under Proprietary. Qwen3.5-122B-A10B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, Kimi K2 Instruct 0905 or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Kimi K2 Instruct 0905 or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Kimi K2 Instruct 0905 and Qwen3.5-122B-A10B?

Kimi K2 Instruct 0905 is available on Fireworks AI and NVIDIA NIM. Qwen3.5-122B-A10B is available on OpenRouter and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.