Qwen3 235B A22B Instruct 2507
alibaba/qwen3-235b-a22b-instruct-2507Par Alibaba (Qwen) · famille: qwen · sorti 2025-07-23 · fin de connaissance: 2025-04
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacités
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding58
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)8/20
- Provider availability10/10
Agents60
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit15/15
- Provider availability10/10
JSON / structured output50
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency79
- Headline price (log-scaled)79/95
- Has prompt-cache pricing0/5
Long context61
- Context window (100K → 2M)51/90
- Has published price for full window10/10
Production-readiness96
- Number of independent providers40/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.55 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $1.10 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.25 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.90 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $1.26 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Détail des tarifs
Tarif recommandé de wandb · Qwen/Qwen3-235B-A22B-Instruct-2507
Fournisseur le moins cher : modelscope · Unknown entrée + Unknown sortie
Disponible chez 18 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| ModelScope modelscope | Qwen/Qwen3-235B-A22B-Instruct-2507 | Unknown | Unknown | 262K | 2025-04-28 |
| 302.AI 302ai | qwen3-235b-a22b-instruct-2507 | $0.290 | $1.14 | 128K | 2025-07-30 |
| Scaleway scaleway | qwen3-235b-a22b-instruct-2507 | $0.750 | $2.25 | 260K | 2025-07-01 |
| Abacus abacus | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.130 | $0.600 | 262K | 2025-07-01 |
| SiliconFlow (China) siliconflow-cn | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.090 | $0.600 | 262K | 2025-07-23 |
| submodel submodel | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.200 | $0.300 | 262K | 2025-08-23 |
| Jiekou.AI jiekou | qwen/qwen3-235b-a22b-instruct-2507 | $0.150 | $0.800 | 131K | 2026-01 |
| NovitaAI novita-ai | qwen/qwen3-235b-a22b-instruct-2507 | $0.090 | $0.580 | 131K | 2025-07-22 |
| Weights & Biases wandb | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.100 | $0.100 | 262K | 2025-04-28 |
| Qiniu qiniu-ai | qwen3-235b-a22b-instruct-2507 | Unknown | Unknown | 262K | 2025-08-12 |
| Nebius Token Factory nebius | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.200 | $0.600 | 262K | 2025-07-25 |
| Venice AI venice | qwen3-235b-a22b-instruct-2507 | $0.150 | $0.750 | 128K | 2025-04-29 |
| Meganova meganova | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.090 | $0.600 | 262K | 2025-07-23 |
| Synthetic synthetic | hf:Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.200 | $0.600 | 256K | 2025-04-28 |
| Friendli friendli | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.200 | $0.800 | 262K | 2025-07-29 |
| Cortecs cortecs | qwen3-235b-a22b-instruct-2507 | $0.062 | $0.408 | 131K | 2025-07-23 |
| SiliconFlow siliconflow | Qwen/Qwen3-235B-A22B-Instruct-2507 | $0.090 | $0.600 | 262K | 2025-07-23 |
| LLM Gateway llmgateway | qwen3-235b-a22b-instruct-2507 | $0.800 | $2.40 | 131K | 2025-07-08 |
Incohérences de données entre fournisseurs
- context_window varies: 128000, 131000, 131072, 256000, 260000, 262000, 262144
- release_date varies (span 248d): 2025-04-28, 2025-04-29, 2025-07-01, 2025-07-08, 2025-07-22, 2025-07-23, 2025-07-25, 2025-07-29, 2025-07-30, 2025-08-12, 2025-08-23, 2026-01
Les fournisseurs rapportent des valeurs différentes pour ce modèle. Les infos clés ci-dessus utilisent un fournisseur représentatif ; voir le tableau pour le détail par fournisseur.
Frequently asked questions
How much does Qwen3 235B A22B Instruct 2507 cost?
Qwen3 235B A22B Instruct 2507 costs $0.100 per 1M input tokens and $0.100 per 1M output tokens, sourced from wandb. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507 has a context window of 262K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen3 235B A22B Instruct 2507 support tool calling?
Yes. Qwen3 235B A22B Instruct 2507 supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Qwen3 235B A22B Instruct 2507 support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen3 235B A22B Instruct 2507 in our data source. Verify with Alibaba (Qwen)'s official documentation before relying on it in production.
Can Qwen3 235B A22B Instruct 2507 accept image input?
No. Qwen3 235B A22B Instruct 2507 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen3 235B A22B Instruct 2507 open-weight?
Yes. Qwen3 235B A22B Instruct 2507's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Qwen3 235B A22B Instruct 2507?
If Qwen3 235B A22B Instruct 2507 doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3-Coder 480B-A35B Instruct. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
Direct comparisons
More Alibaba (Qwen) models
- Qwen3.5 397B-A17B$0.60 in / $3.60 out
- Qwen3 32B$0.70 in / $2.80 out
- Qwen3-Coder 480B-A35B Instruct$1.50 in / $7.50 out
- Qwen3-235B-A22B-Thinking-2507$0.10 in / $0.10 out
- Qwen3-Next 80B-A3B Instruct$0.50 in / $2.00 out
Capability lists this model is in
Dernière mise à jour :
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.