Mixtral 8x7B Instruct v0.1 vs Qwen3.6-35B-A3B

Mixtral 8x7B Instruct v0.1 (2023) and Qwen3.6-35B-A3B (2026) compare a standalone API model against a coding-specialized model. Mixtral 8x7B Instruct v0.1 ships a 33k-token context window, while Qwen3.6-35B-A3B ships a 262k-token context window. On pricing, both list $0.15/1M input tokens on the cheapest tracked route. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Mixtral 8x7B Instruct v0.1 is standalone API model, while Qwen3.6-35B-A3B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first

Signal	Mixtral 8x7B Instruct v0.1	Qwen3.6-35B-A3B	How to read it
Product type	Standalone API model	Coding-specialized model	Read downstream rows through the product-type lens before comparing benchmarks, prices, or provider availability.
Best for	provider-routed production	custom coding agents, code generation, and tool loops	Use-case synthesis from product type, capability flags, context, and provider data.
Decision fit	General	Coding, RAG, and Agents	Primary workload tags from local decision data.
Context window	33k	262k	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$0.45/1M tokens	$1/1M tokens	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	5 tracked	2 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	0 rows	0 rows	No shared benchmark rows are sourced for this pair yet.

Decision tradeoffs

Choose Mixtral 8x7B Instruct v0.1 when...

Mixtral 8x7B Instruct v0.1 has the lower cheapest tracked output price at $0.45/1M tokens.
Mixtral 8x7B Instruct v0.1 has broader tracked provider coverage for fallback and procurement flexibility.

Choose Qwen3.6-35B-A3B when...

Qwen3.6-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
Qwen3.6-35B-A3B uniquely exposes Vision, Multimodal, and Function calling in local model data.
Local decision data tags Qwen3.6-35B-A3B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Mixtral 8x7B Instruct v0.1

Requests / monthInput tokens / requestOutput tokens / request

Mixtral 8x7B Instruct v0.1

$233

Cheapest tracked route/tier: DeepInfra

Qwen3.6-35B-A3B

$370

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $138. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Mixtral 8x7B Instruct v0.1 -> Qwen3.6-35B-A3B

No overlapping tracked provider route is sourced for Mixtral 8x7B Instruct v0.1 and Qwen3.6-35B-A3B; plan for SDK, billing, or endpoint changes.
Qwen3.6-35B-A3B is $0.55/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Qwen3.6-35B-A3B adds Vision, Multimodal, and Function calling in local capability data.

Qwen3.6-35B-A3B -> Mixtral 8x7B Instruct v0.1

No overlapping tracked provider route is sourced for Qwen3.6-35B-A3B and Mixtral 8x7B Instruct v0.1; plan for SDK, billing, or endpoint changes.
Mixtral 8x7B Instruct v0.1 is $0.55/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification	Mixtral 8x7B Instruct v0.1 MistralAI	Qwen3.6-35B-A3B Alibaba
Released	2023-12-10	2026-04-16
Context window	33k	262k
Parameters	56B	35B
Architecture	decoder only	moe
License	Apache 2.0(OSI)	Apache 2.0(OSI)
Openness	Open source	Open source
Commercial use	Commercial use allowed	Commercial use allowed
Knowledge cutoff	2023-12	-

Pricing and availability

Pricing attribute	Mixtral 8x7B Instruct v0.1	Qwen3.6-35B-A3B
Input price	$0.15/1M tokens	$0.15/1M tokens
Output price	$0.45/1M tokens	$1/1M tokens
Providers	Together AI OctoML (Deprecated)AWS Bedrock IBM watsonx DeepInfra	OpenRouter Novita AI

Capabilities

Capability	Mixtral 8x7B Instruct v0.1	Qwen3.6-35B-A3B
Vision	No	Yes
Multimodal	No	Yes
Reasoning	No	No
Function calling	No	Yes
Tool use	No	Yes
Structured outputs	No	No
Code execution	No	No
IDE integration	No	No
Computer use	No	No
Parallel agents	No	No

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Qwen3.6-35B-A3B, multimodal input: Qwen3.6-35B-A3B, function calling: Qwen3.6-35B-A3B, and tool use: Qwen3.6-35B-A3B. 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, Mixtral 8x7B Instruct v0.1 lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider, while Qwen3.6-35B-A3B lists $0.15/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B Instruct v0.1 lower by about $0.16 per million blended tokens. Availability is 5 providers versus 2, so concentration risk also matters.

Choose Mixtral 8x7B Instruct v0.1 when provider fit and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support and larger context windows 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, Mixtral 8x7B Instruct v0.1 or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B supports 262k tokens, while Mixtral 8x7B Instruct v0.1 supports 33k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Mixtral 8x7B Instruct v0.1 or Qwen3.6-35B-A3B?

Mixtral 8x7B Instruct v0.1 is cheaper on tracked token pricing. Mixtral 8x7B Instruct v0.1 costs $0.15/1M input and $0.45/1M output tokens. Qwen3.6-35B-A3B costs $0.15/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Mixtral 8x7B Instruct v0.1 or Qwen3.6-35B-A3B open source?

Mixtral 8x7B Instruct v0.1 is listed under Apache 2.0. Qwen3.6-35B-A3B 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, Mixtral 8x7B Instruct v0.1 or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B 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, Mixtral 8x7B Instruct v0.1 or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B 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 Mixtral 8x7B Instruct v0.1 and Qwen3.6-35B-A3B?

Mixtral 8x7B Instruct v0.1 is available on Together AI, OctoML (Deprecated), AWS Bedrock, IBM watsonx, and DeepInfra. Qwen3.6-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.

Both models

Mixtral 8x7B Instruct v0.1 Qwen3.6-35B-A3B