Qwen3.5 35B A3B vs Jev
At a Glance
| Compare |  Qwen3.5 35B A3BQwen |  JevTypeSafe |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.14Deepinfra ↗ · Sep 22, 2026 | $0.042TypeSafe ↗ · Sep 17, 2026 |
| Output priceFrom · USD / 1M tokens | $1.00Deepinfra ↗ · Sep 22, 2026 | $0.000TypeSafe ↗ · Sep 17, 2026 |
| Context windowMaximum documented tokens | 262K | 64K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 17, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Qwen3.5-35B-A3B | Jev |
|---|---|---|
| Developer | Qwen | TypeSafe |
| Family | Qwen3 5 35b A3b | Jev |
| Model | Qwen3.5-35B-A3B | Jev |
| Version | Qwen3.5-35B-A3B | Jev |
| Lifecycle | active | active |
| Released | Unknown | 2026-09-15 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Model-specific input |
| Output modalities | Text | Model-specific input |
| Context window | 262K | 64K |
| Total parameters | 36B | Unknown |
| Active parameters | 3B | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | TypeSafe (Standard) |
| Capabilities | chat, generation, reasoning, tools | calibrated-confidence, parallel-evaluation, structured_outputs, typed-decisions |
| Maximum Choice cardinality | Unknown | 255 options |
| Default request rate limit | Unknown | 1200 requests per minute |
| State plus longest question limit | Unknown | 32000 tokens |
| Combined state and questions limit | Unknown | 64000 tokens |
| Default token rate limit | Unknown | 250000 tokens per second |
Qwen3.5 35B A3B Capabilities
Jev Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Qwen3.5-35B-A3BQwen | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Grok 4.6xAI | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Qwen3.8-MaxQwen | family variantsimage, text |
Qwen3.5-35B-A3BQwen | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | Qwen3.5-35B-A3BQwen | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs |  Hy4 previewTencent | cross-developer peerstext |
Qwen3.5-35B-A3BQwen | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 35B A3B vs Jev FAQs
Is Qwen3.5 35B A3B or Jev better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 35B A3B and Jev, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 35B A3B or Jev?+
Qwen3.5 35B A3B is $0.14 and Jev is $0.042 per million tokens, so Jev is cheaper on this metric. Qwen3.5 35B A3B is $1.00 and Jev is $0.000 per million tokens, so Jev is cheaper on this metric.
Which has a larger context window, Qwen3.5 35B A3B or Jev?+
Qwen3.5 35B A3B has the larger sourced context window. Qwen3.5 35B A3B supports 262K and Jev supports 64K.
Which performs better in benchmarks, Qwen3.5 35B A3B or Jev?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5 35B A3B or Jev be self-hosted?+
Qwen3.5 35B A3B is the only model in this pair currently marked as self-hostable. Qwen3.5 35B A3B is open weight; Jev is not marked open weight.
Can Qwen3.5 35B A3B and Jev understand images?+
Qwen3.5 35B A3B is documented with image input; Jev is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 35B A3B or Jev?+
Neither has a larger sourced maximum output. Qwen3.5 35B A3B is — and Jev is —.
Do Qwen3.5 35B A3B and Jev support reasoning and tool use?+
Qwen3.5 35B A3B: reasoning, tool calling, and image input. Jev: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 35B A3B or Jev?+
Qwen3.5 35B A3B has 4 sourced provider routes; Jev has 1, so Qwen3.5 35B A3B has broader tracked availability.
Which offers better value, Qwen3.5 35B A3B or Jev?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.