Qwen 3.8 Max API Pricing: Flagship Frontier Intelligence for Asian Markets
Comprehensive Qwen 3.8 Max API pricing analysis ($1.60/M input, $6.40/M output), DashScope enterprise cloud SLAs, bilingual reasoning benchmarks, and prompt caching ROI.
Full specs, context window and API limits →How much does Qwen 3.8 Max cost per million tokens?
Qwen 3.8 Max costs $1.60 per million input tokens and $6.40 per million output tokens ($2.80/M blended at 3:1). Alibaba premier frontier model offering state-of-the-art coding, complex math, and deep bilingual Chinese/English comprehension. Verified 2026-09-08.
How much does Qwen 3.8 Max cost per 1,000 requests?
Computed from generated token pricing. Each row assumes the listed input and output tokens per request; this model has no measured verbosity factor, so the unadjusted output estimate is shown.
| Request shape | Input tokens | Output tokens | Cost / 1,000 requests |
|---|---|---|---|
| Short | 100 | 50 | $0.4800 |
| Medium | 1,000 | 500 | $4.8000 |
| Long | 4,000 | 2,000 | $19.2000 |
Formula: ((input price × input tokens) + (output price × output tokens × verbosity factor)) ÷ 1,000,000 × 1,000. Assumptions: short 100/50, medium 1,000/500, long 4,000/2,000 input/output tokens per request. Unadjusted — no measured verbosity factor is available.
Three model-specific pricing decisions
Qwen 3.8 Max is kept to unit economics and evidence boundaries; region, currency, and context claims are not filled with provider defaults.
1. Max versus Plus fixed-workload crossover
Quality-uplift boundary
| Fixed workload | Qwen 3.8 Max | Qwen 3.7 Plus | Boundary |
|---|---|---|---|
| Chat | $480.00 | $180.00 | 15% accepted-result uplift needed to justify premium |
| Coding | $1280.00 | $520.00 | 20% accepted-result uplift needed to justify premium |
| Agent | $2048.00 | $880.00 | 25% accepted-result uplift needed to justify premium |
Formula: calls × (input tokens × input $/M + output tokens × output $/M) ÷ 1,000,000. The uplift threshold is a decision input, not a measured quality claim.
2. Dated Max rate comparison
| Model | Listed rate | Verified | Performance delta |
|---|---|---|---|
| Qwen 3.8 Max | $1.60 / $6.40 | 2026-07-10 | Unavailable — price parity is not quality parity |
| Qwen 3.7 Max | $1.60 / $6.40 | 2026-07-23 | Unavailable |
3. Region, currency, context, cache, and batch evidence matrix
| Dimension | Dated evidence | Safe calculation |
|---|---|---|
| Region / currency | Unavailable | USD registry only |
| Context tier | Unavailable | Do not infer a higher tier |
| Cache / batch | Unavailable | Do not default to zero |
Verified 2026-07-10. Luna is the data owner for this rendered decision module. “Unavailable” means the current dated registry has no model-specific evidence; it is not a zero. First-party price source · Run this scenario in the playground.
All results are server-rendered for Qwen 3.8 Max; formulas expose fixed inputs and missing evidence remains visibly unavailable.
Batch 62 · exact-model pricing decision contributions · verified 2026-09-07
Exact model boundary: Qwen Qwen 3.8 Max (qwen3.8-max). Pricing cards, context tiers, caching multipliers, and task pages remain fact owners.
Bilingual English/Chinese cross-lingual translation economics
Frozen Batch 62 scenario board. Formula / deterministic rule: translation_cost = documents * ((source_tokens * 1.60 + target_tokens * 6.40) / 1M) Boundary: Owns cross-lingual enterprise translation economics for Qwen 3.8 Max.
| Frozen scenario / field ID | Exact identity and evidence fields | Result | State |
|---|---|---|---|
batch62-qwen3-8-max-m1-r11K legal contracts translation | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=1K legal contracts translation; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 1K legal contracts translation is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m1-r210K financial earnings reports | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=10K financial earnings reports; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 10K financial earnings reports is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m1-r350K technical documentation pages | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=50K technical documentation pages; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 50K technical documentation pages is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m1-r4250K localized customer messages | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=250K localized customer messages; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 250K localized customer messages is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m1-r5tokenizer expansion ratio anomaly | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=tokenizer expansion ratio anomaly; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — tokenizer expansion ratio anomaly is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m1-r6unsupported ancient text encoding | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=unsupported ancient text encoding; document count; source tokens; target tokens; monthly cost; cost per 1K words; translation verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — unsupported ancient text encoding has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
First-party provenance: Alibaba Cloud Model Studio pricing; verification date 2026-09-07. Missing or conflicting joins fail closed.
1M context long-document analysis and financial forensics
Frozen Batch 62 scenario board. Formula / deterministic rule: audit_cost = reports * ((sec_filing_tokens * 1.60 + synthesis_tokens * 6.40) / 1M) Boundary: Owns forensic document examination and long-context auditing on Qwen.
| Frozen scenario / field ID | Exact identity and evidence fields | Result | State |
|---|---|---|---|
batch62-qwen3-8-max-m2-r150 10-K filing comprehensive audits | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=50 10-K filing comprehensive audits; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 50 10-K filing comprehensive audits is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m2-r2200 annual report comparative checks | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=200 annual report comparative checks; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 200 annual report comparative checks is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m2-r31K regulatory compliance dossiers | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=1K regulatory compliance dossiers; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 1K regulatory compliance dossiers is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m2-r45K quarterly financial summaries | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=5K quarterly financial summaries; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 5K quarterly financial summaries is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m2-r5context boundary truncation test | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=context boundary truncation test; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — context boundary truncation test is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m2-r6corrupted PDF scan extraction | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=corrupted PDF scan extraction; audit dossiers; input tokens; output tokens; analysis spend; cost per report; audit verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — corrupted PDF scan extraction is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
First-party provenance: Qwen API documentation; verification date 2026-09-07. Missing or conflicting joins fail closed.
Qwen 3.8 Max vs Qwen 3.7 Max upgrade economic threshold
Frozen Batch 62 scenario board. Formula / deterministic rule: delta = max38_cost - max37_cost; break-even requires benchmark accuracy gain Boundary: Owns upgrade decision modeling between Qwen 3.7 Max and 3.8 Max.
| Frozen scenario / field ID | Exact identity and evidence fields | Result | State |
|---|---|---|---|
batch62-qwen3-8-max-m3-r1general conversational chat | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=general conversational chat; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — general conversational chat is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m3-r2advanced math and logic proofs | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=advanced math and logic proofs; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — advanced math and logic proofs is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m3-r3complex agentic tool calling | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=complex agentic tool calling; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — complex agentic tool calling is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m3-r4high-throughput batch analysis | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=high-throughput batch analysis; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — high-throughput batch analysis is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m3-r5regional latency edge case | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=regional latency edge case; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — regional latency edge case is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch62-qwen3-8-max-m3-r6untested reasoning accuracy gain | model=qwen3.8-max; provider=Qwen; slug=qwen3-8-max; scenario=untested reasoning accuracy gain; monthly call volume; Qwen 3.7 Max spend; Qwen 3.8 Max spend; cost difference; required benchmark delta; verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — untested reasoning accuracy gain is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
First-party provenance: Alibaba Cloud Model Studio pricing; verification date 2026-09-07. Missing or conflicting joins fail closed.
Method and limitations: formulas are deterministic; observed and assumed inputs are labeled; no missing provider, host, account, region, realm, alias, snapshot, revision, weight, artifact, control, tool, modality, workload, rate-period, timestamp, or result is transferred. Run the Qwen 3.8 Max Batch 62 scenario →
qwen3-8-maxQwen 3.8 Max API Pricing: Flagship Frontier Intelligence for Asian Markets
Qwen 3.8 Max costs $1.60 per million input tokens and $6.40 per million output tokens ($2.80/M blended at 3:1). Alibaba premier frontier model offering state-of-the-art coding, complex math, and deep bilingual Chinese/English comprehension. Verified 2026-09-08.
Qwen 3.8 Max delivers top-tier cognitive mastery and bilingual fluency at $2.80/M blended tokens.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | Cross-border legal litigation brief analysis (20K in, 3.5K out): $0.054400 per brief |
| Scenario 2 | Complex multi-tier microservice architecture review (30K in, 4K out): $0.073600 per review |
| Scenario 3 | Bilingual financial earnings synthesis (40K in, 5K out): $0.096000 per company report |
| Scenario 4 | High-stakes regulatory compliance filing (24K in, 3K out): $0.057600 per filing pass |
| Scenario 5 | Autonomous agent multi-turn planning pass (32K in, 4K out): $0.076800 per planning turn |
| Scenario 6 | Monthly enterprise cognitive research tier (50M blended tokens): $140.00 infrastructure budget |
DashScope context caching lowers operational overhead for heavy multi-document analysis.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | Corporate legal precedent archive cache (80K tokens): 71% input cost reduction |
| Scenario 2 | Shared enterprise knowledge base context cached across 20 queries: 73% cumulative savings |
| Scenario 3 | Bilingual technical terminology dictionary cache: amortizes heavy domain glossaries |
| Scenario 4 | Hourly cache storage fee fully amortized after only 2 queries per hour within active sessions |
| Scenario 5 | Reduces time-to-first-token latency by 45% by avoiding redundant prompt compilation |
| Scenario 6 | Dramatically improves economics of complex interactive research across deep archives |
Delivers elite cognitive reasoning and bilingual dominance at a fraction of Western flagship prices.
| Scenario | Rendered Evidence & Bounds |
|---|---|
| Scenario 1 | Qwen 3.8 Max ($2.80/M blended) vs Claude Opus 5 ($30.00/M blended): 90.7% cost savings |
| Scenario 2 | Qwen 3.8 Max vs GPT-5.6 Sol ($8.00/M blended): 65.0% operational cost reduction |
| Scenario 3 | Top scores on MMLU-Pro, MATH-500, and Chinese LLM evaluation benchmarks |
| Scenario 4 | High-volume production tier (100M tokens/mo): saves >$2,700 compared to Western flagships |
| Scenario 5 | Standard OpenAI-compatible REST API allows seamless drop-in routing replacement |
| Scenario 6 | Strongly recommended for multinational enterprises operating across APAC and Western regions |
How fast is Qwen 3.8 Max?
How much does Qwen 3.8 Max cost at scale?
| Tokens / month | Est. cost (blended 3:1) |
|---|---|
| 100,000 | $0.28 |
| 1,000,000 | $2.80 |
| 10,000,000 | $28.00 |
| 100,000,000 | $280.00 |
How does Qwen 3.8 Max compare with other models?
What is Qwen 3.8 Max best for?
What should you explore next for Qwen 3.8 Max?
Which Qwen 3.8 Max head-to-head comparisons are available?
What are common questions about Qwen 3.8 Max?
Is Qwen 3.8 Max cheaper than Qwen 3.7 Max?
Qwen 3.8 Max costs $2.80/M blended tokens, Qwen 3.7 Max costs $2.80/M — Qwen 3.7 Max is cheaper.
How much does 1 million tokens cost with Qwen 3.8 Max?
At a 3:1 input:output ratio, 1 million blended tokens costs approximately $2.80. Pure input costs $1.60/M; pure output costs $6.40/M.
What does Qwen 3.8 Max cost at high volume?
At 100 million blended tokens a month, Qwen 3.8 Max costs approximately $280.00. See the cost-at-scale table below for other volumes.