Three of the four cheap-tier models worth comparing right now shipped or changed price in the last two weeks: Gemini 3.8 Flash and Muse Spark 1.3 both landed on 2 September 2026, GLM-5.3-Flash on 26 August, with DeepSeek V4 Flash the incumbent, quietly re-post-trained in July. Here they are in one table — with the caveats that make the table honest.
What are the cheapest fast LLM APIs in 2026?
Every figure below was read off the vendor's own pricing page on 3 September 2026. Prices are USD per 1M tokens.
| Model | Input | Cached input | Output | Context | Max output | Accepts |
|---|---|---|---|---|---|---|
| GLM-5.3-Flash (promo) | $0.075 | $0.015 | $0.25 | 1M | 128K | text, image, video, file |
| GLM-5.3-Flash (list) | $0.15 | $0.03 | $0.50 | 1M | 128K | text, image, video, file |
| Muse Spark 1.3 Contributor | $0.10 | $0.002 | $0.20 | 1,048,576 | 943,718 | text, image, video, file, audio |
| Muse Spark 1.3 (standard) | $1.25 | $0.15 | $4.25 | 1,048,576 | 943,718 | text, image, video, file, audio |
| DeepSeek V4 Flash (off-peak) | $0.22 | $0.007 | $0.66 | 1M | 384K | text only |
| DeepSeek V4 Flash (peak) | $0.44 | $0.014 | $1.32 | 1M | 384K | text only |
| Gemini 3.8 Flash | $0.75 | $0.075 | $3.75 | 1,048,576 | 65,536 | text, image, video, PDF, audio |
| Gemini 3.8 Flash (batch) | $0.375 | $0.0375 | $1.875 | 1,048,576 | 65,536 | text, image, video, PDF, audio |
The spread on output tokens between GLM-5.3-Flash at its promotional rate and Gemini 3.8 Flash is 15×. Against DeepSeek's peak-hour rate it is 5×. That is a big enough gap that it deserves an explanation, and "Google charges more because it's Google" is not the explanation.
One thing the headline table hides: DeepSeek V4 Flash costs less if you don't buy it from DeepSeek. The weights are MIT-licensed, so third-party hosts serve the same model far below DeepSeek's own API. On OpenRouter, DigitalOcean lists it at $0.068/$0.168 and DeepInfra at $0.09/$0.18 — roughly a third of DeepSeek's own $0.22/$0.66 off-peak rate, and about a fifth of the peak rate. If you saw "DeepSeek V4 Flash costs $0.089 per million" quoted somewhere, that was a reseller's price, not the vendor's.
What does the price difference actually buy you?
Four things, and only one of them is raw intelligence.
Throughput. Artificial Analysis measures Gemini 3.8 Flash at 298.6 output tokens per second against GLM-5.3-Flash's 44.6. That is a 6.7× gap. If you are streaming into a user-facing chat window, the cheap model feels slow in a way a spreadsheet won't show you.
But not latency. The inversion is genuinely interesting: Gemini 3.8 Flash's time to first token is 13.21 seconds at high reasoning effort, against 1.65s for GLM-5.3-Flash and 1.50s for DeepSeek V4 Flash. Gemini spends a long time thinking, then writes very fast. For short answers the cheap models win the perceived-speed race outright; for long generations Gemini catches up and passes.
Max output. This is the most under-discussed number in the table. Gemini 3.8 Flash caps completions at 65,536 tokens. Muse Spark 1.3 allows 943,718 — a 14× difference. DeepSeek sits at 384K, GLM at 128K. If your job is "translate this book" or "emit a 200-page structured report in one call", Gemini structurally cannot do it and you will be writing chunking logic instead.
Modalities. Gemini 3.8 Flash and both Muse Spark tiers accept audio and video. GLM-5.3-Flash accepts image, video and files but not audio. DeepSeek V4 Flash is text only — its vision capability lives in a separate experimental model, deepseek-v4-flash-vision-exp. If you are transcribing calls or reading video, two of these four are simply not candidates.
On the boring-but-essential stuff, all four are equivalent: every one supports tool calling, JSON mode and structured outputs. DeepSeek additionally exposes an Anthropic-format endpoint and FIM completion, and publishes a concurrency limit of 2,500 for V4 Flash against 500 for V4 Pro — one of the few rate limits any of these vendors state numerically.
How do they compare on benchmarks?
Keep vendor claims and independent measurement separate, because they disagree in predictable directions.
Vendor-published. Z.ai reports GLM-5.3-Flash at 63.4 on DeepSWE v1.1 (up from 46.2 for GLM-5.2) and 48.8 on AutomationBench (up from 26.2). It also reports 29.0 on its own Z.ai Code Bench v1.0 at max effort, against 29.5 for Claude Opus 4.8 — a near-tie the company is understandably keen to highlight, on a benchmark the company itself maintains. Google describes Gemini 3.8 Flash as "our most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows" without publishing a comparison table we could locate.
Independent. On Artificial Analysis's Intelligence Index v4.1.1, which aggregates nine evaluations including Terminal-Bench v2.1, GPQA Diamond, SciCode and Humanity's Last Exam:
| Model | Intelligence Index | Output speed | Time to first token |
|---|---|---|---|
| Muse Spark 1.3 (max) | 62 | not published | not published |
| Gemini 3.8 Flash (high) | 59 | 298.6 tok/s | 13.21s |
| GLM-5.3-Flash | 57 | 44.6 tok/s | 1.65s |
| DeepSeek V4 Flash 0731 | 52 | 136.1 tok/s | 1.50s |
The headline: a 19× output-price gap buys two points of Intelligence Index. Muse Spark 1.3 tops the group, but Artificial Analysis measured the standard tier and publishes no speed data for it at all, so treat that 62 as a capability ceiling rather than a production promise.
What is the real cost per completed task?
Per-token price is the wrong unit. A model that reasons more, retries more, or rambles more can be cheaper per token and more expensive per finished job. Artificial Analysis publishes the actual dollar cost of running its full evaluation suite against each model, which is the closest thing to a like-for-like cost-per-task figure that exists:
| Model | Cost to run the Intelligence Index | Index score | Output tokens emitted |
|---|---|---|---|
| GLM-5.3-Flash | $138.02 | 57 | 150M (median 110M) |
| DeepSeek V4 Flash 0731 | $323.26 | 52 | 210M (median 110M) |
| Gemini 3.7 Flash (high) | $484.73 | 56 | 64M (median 71M) |
| Gemini 3.8 Flash (high) | $825.83 | 59 | 120M (median 71M) |
| Muse Spark 1.3 (max) | not published | 62 | 120M |
A caveat on reading that table: the "median" figures come from different comparison cohorts, so 150M-against-110M and 120M-against-71M are not the same kind of statement. And Artificial Analysis publishes no evaluation cost for Muse Spark 1.3 at all, so its cost per task is genuinely unknown — we have its capability score and its token consumption, but no way to price the run. Three findings fall out of what is measurable.
First, DeepSeek V4 Flash is verbose enough to erase its price advantage. It emitted 210M output tokens to complete the suite — nearly double the 110M median — which is why a model with cheap tokens ends up costing 2.3× more per task than GLM-5.3-Flash while scoring five points lower. This is exactly the trap the brief-level price comparison sets for you.
Second, Artificial Analysis priced GLM at list, not promo. Its $138.02 figure uses $0.15/$0.50. At the current promotional $0.075/$0.25 the same run would cost roughly $69 — and Z.ai's own documentation claims "$0.045 per task (discounted)" on this suite. So GLM's cost-per-task lead over Gemini is somewhere between 6× and 12× depending on whether you catch the promotion.
Third, and this is the cleanest proof that per-token pricing is close to meaningless for reasoning models: Gemini 3.7 Flash and Gemini 3.8 Flash have identical sticker prices — both $0.75/$3.75 — yet running the same evaluation suite costs $484.73 on 3.7 and $825.83 on 3.8. The newer model emits 88% more output tokens (120M vs 64M), and because thinking tokens bill at the full output rate, that verbosity flows straight to your invoice. You pay 1.7× per completed task for three points of Intelligence Index, and no price list anywhere would have told you. If you are cost-sensitive and 56 is enough, 3.7 Flash is the better buy at the same headline rate.
What are the strings attached to the headline prices?
All four headline rates come with a condition. A price table that omits them is actively misleading.
GLM-5.3-Flash's rate is promotional and expires this week. Z.ai's pricing page states plainly: "GLM-5.3-Flash is available at a 50% discount (strikethrough prices are list prices). The promotion ends at 24:00 on September 9, 2026 (UTC+8, Singapore time)." List price is $0.15/$0.50. Cached-input storage is separately marked "Limited-time Free". You can watch this expiry in real time on OpenRouter: Z.ai's own endpoint serves the model at $0.075/$0.25, while roughly twenty third-party hosts of the same open weights all sit at exactly $0.15/$0.50.
Muse Spark Contributor is paid for with your data. The Contributor tier is 12.5× cheaper on input and 21× cheaper on output than standard Muse Spark 1.3. The listed condition is a single sentence: "Prompts and outputs may be used to improve Meta's products." That disclosure appears on the Contributor tier and is absent from the standard tier, which is the whole difference between them. Meta's full terms live behind its developer terms of service, and we could not extract clause-level detail on retention or human review, so treat the scope as unbounded until you have read them yourself. Practical reading: do not put client code, customer PII, or anything under HIPAA/GDPR-style obligations through the Contributor tier. For your own side project, it is the best price-to-capability ratio on this page.
DeepSeek doubles its price on weekday mornings. Its pricing page footnote reads: "Off-peak rates are half of the peak rates. Peak hours are 01:00 – 04:00 and 06:00 – 10:00 UTC, Monday through Friday (all other hours are off-peak)." That is seven hours a day, five days a week, at 2× — and those windows land squarely on European working hours. If your batch jobs can be shifted outside them you halve your bill; if you are serving live European traffic you will pay peak most of the time. We covered the mechanics of this in our DeepSeek V4 pricing guide.
Gemini 3.8 Flash's price is introductory and doubles in four months. This is the one almost nobody has noticed. Google's pricing page lists input as "$0.75 through December 31, 2026. $1.50 starting January 1, 2027" and output as "$3.75 through December 31, 2026. $7.50 starting January 1, 2027". Cache reads go $0.075 → $0.15 and cache storage $0.50 → $1.00 per million tokens per hour on the same date. Gemini 3.7 Flash sits on the same introductory schedule at the same rate. Note also that the output price explicitly includes thinking tokens, and Gemini 3.8 Flash thinks a lot — that 13.21s time to first token is billed at the output rate. Between the January doubling and 3.8's 88% higher token consumption, a Gemini-based cost model built on today's numbers understates next year's bill by roughly 3×.
What do these models cost on three real workloads?
Prices below use each vendor's current rate, no caching except where stated.
1. High-volume classification. 10M requests/month, 400 input tokens and 30 output tokens each (4B in, 300M out):
- GLM-5.3-Flash (promo): $375 — list price $750
- DeepSeek V4 Flash via a third-party host at $0.09/$0.18: $414
- Muse Spark Contributor: $460
- DeepSeek V4 Flash, first-party off-peak: $1,078 — $2,156 at peak
- Gemini 3.8 Flash, batch API: $2,063 — $4,125 synchronous
Input-dominated work punishes Gemini hardest, because its input premium is 10× GLM's. Use the batch API if you land here.
2. A coding agent. 1,000 sessions/month, each reading 2M tokens of context (80% cache hits) and writing 120K tokens:
- Muse Spark Contributor: $67 (its $0.002 cache-read rate is the lowest here by 7×)
- GLM-5.3-Flash (promo): $84 — list price $168
- DeepSeek V4 Flash, first-party off-peak: $178 — $357 at peak
- Gemini 3.8 Flash: $870, plus cache storage at $0.50 per million tokens per hour, which on a 1.6M-token working set held for an eight-hour day is real money
- Muse Spark 1.3 standard: $1,250
Agent workloads are cache-read dominated, which is where the four models diverge most violently — a 75× spread between Muse Contributor's cache rate and Muse standard's.
3. Long-document processing. 50,000 documents/month at 300K input and 8K output each (15B in, 400M out):
- GLM-5.3-Flash (promo): $1,225 — list price $2,450
- DeepSeek V4 Flash via third-party host: $1,422
- Muse Spark Contributor: $1,580
- DeepSeek V4 Flash, first-party off-peak: $3,564
- Gemini 3.8 Flash, batch: $6,375 — $12,750 synchronous
The caveat that overrides the numbers: if "documents" means scanned PDFs with audio attachments, only Gemini and Muse can read them at all, and the comparison collapses to those two.
Can you self-host any of these models?
Two of the four, not one. Both GLM-5.3-Flash and DeepSeek V4 Flash publish open weights under the MIT licence on Hugging Face — GLM-5.3-Flash at 320B total parameters with 18B active, using a hybrid sparse-and-linear attention architecture, and DeepSeek V4 Flash at 284B total with 13B active in mixed FP4/FP8 precision. Gemini 3.8 Flash and Muse Spark are API-only.
That matters for the Contributor-tier problem: if your blocker is data governance rather than price, self-hosting an MIT-licensed model is the exit. It is not cheap at these parameter counts — you are provisioning multi-GPU nodes for a 320B MoE — but it is the only option where no third party sees your prompts. Our walkthrough is here: how to run GLM-5.3-Flash locally.
Which cheap model should you actually pick?
The decision rule, in order:
- Need audio or video input? Gemini 3.8 Flash or Muse Spark. The other two are out at step one.
- Need to emit more than 128K tokens in one call? Muse Spark (943K) or DeepSeek (384K). Gemini's 65K ceiling is the tightest here.
- Is the data sensitive? Rule out Muse Spark Contributor. Consider self-hosting GLM-5.3-Flash or DeepSeek V4 Flash.
- Otherwise, default to GLM-5.3-Flash — best measured cost per task, fastest time to first token of the group bar DeepSeek, MIT weights as an escape hatch. Just budget at the $0.15/$0.50 list price, not the promo.
| If you're doing this | Pick | Because |
|---|---|---|
| High-volume text classification | GLM-5.3-Flash | Lowest input price of any capable model here |
| A coding or long-horizon agent | GLM-5.3-Flash | Best cost per completed task; strong DeepSWE scores |
| User-facing streaming chat | Gemini 3.8 Flash | 298 tok/s output — 6.7× the cheap models |
| Audio/video ingestion | Gemini 3.8 Flash | Only mature option with audio input |
| Very long single generations | Muse Spark 1.3 | 943K max output vs Gemini's 65K |
| Personal projects, non-sensitive | Muse Spark Contributor | Index 62 capability at $0.10/$0.20 |
| Off-hours batch text jobs | DeepSeek V4 Flash | Off-peak halving, if you avoid its verbosity |
| Regulated or client data | Self-hosted GLM or DeepSeek | MIT weights, no third party sees prompts |
There is no free lunch in this table, only differently-shaped bills. GLM-5.3-Flash wins on measured cost per task today and still wins at list price next week. Gemini 3.8 Flash earns its premium only if throughput or audio is what you're buying — and plan for the January doubling. Muse Spark Contributor is the best deal here for anything you'd be comfortable posting publicly, and unusable for anything else. DeepSeek V4 Flash is the one to buy from someone other than DeepSeek.
Deeper single-model breakdowns: GLM-5.3-Flash, Gemini 3.8 Flash, Muse Spark 1.3, and DeepSeek V4 Flash.
FAQ
What is the cheapest LLM API in 2026?
Among capable fast-tier models, GLM-5.3-Flash is cheapest at $0.075 input and $0.25 output per million tokens, though that is a 50% promotion expiring 9 September 2026; list price is $0.15/$0.50. Muse Spark 1.3 Contributor is close at $0.10/$0.20 but requires granting Meta rights to use your prompts and outputs.
Is GLM-5.3-Flash really cheaper than Gemini Flash?
Yes, substantially. GLM-5.3-Flash costs $0.25 per million output tokens against Gemini 3.8 Flash's $3.75 — a 15× gap. More importantly it is cheaper per completed task: Artificial Analysis spent $138.02 running its Intelligence Index on GLM-5.3-Flash versus $825.83 on Gemini 3.8 Flash, for scores of 57 and 59 respectively.
What is the Muse Spark Contributor tier?
It is Meta's discounted access tier for Muse Spark 1.3, priced at $0.10 input and $0.20 output per million tokens against $1.25/$4.25 for the standard tier. The listed condition is that "prompts and outputs may be used to improve Meta's products". The standard tier carries no such disclosure. Avoid Contributor for client code, personal data, or regulated workloads.
Which cheap model is best for coding?
GLM-5.3-Flash on current evidence. Z.ai reports 63.4 on DeepSWE v1.1 and 48.8 on AutomationBench, and it delivers the lowest independently measured cost per task of the four. DeepSeek V4 Flash is a reasonable alternative for text-only work but scored 52 on the Intelligence Index while emitting 210M output tokens — nearly double the median — which inflates real-world cost.
Which cheap models support audio and video?
Gemini 3.8 Flash and both Muse Spark 1.3 tiers accept text, image, video, PDF and audio input. GLM-5.3-Flash accepts text, image, video and files but not audio. DeepSeek V4 Flash is text-only; its vision capability is a separate experimental model called deepseek-v4-flash-vision-exp. All four output text only.
Is DeepSeek V4-Flash pricing always the same?
No. DeepSeek applies peak pricing at 2× the off-peak rate during 01:00–04:00 and 06:00–10:00 UTC, Monday to Friday. Off-peak is $0.22 input and $0.66 output per million tokens; peak is $0.44 and $1.32. Third-party hosts of the MIT-licensed weights charge a flat rate around $0.09/$0.18 with no peak surcharge.